genproto: google.golang.org/genproto/googleapis/cloud/bigquery/v2 Index | Files

package bigquery

import "google.golang.org/genproto/googleapis/cloud/bigquery/v2"

Index

Package Files

encryption_config.pb.go model.pb.go model_reference.pb.go standard_sql.pb.go table_reference.pb.go

Variables

var (
    Model_ModelType_name = map[int32]string{
        0:  "MODEL_TYPE_UNSPECIFIED",
        1:  "LINEAR_REGRESSION",
        2:  "LOGISTIC_REGRESSION",
        3:  "KMEANS",
        4:  "MATRIX_FACTORIZATION",
        5:  "DNN_CLASSIFIER",
        6:  "TENSORFLOW",
        7:  "DNN_REGRESSOR",
        9:  "BOOSTED_TREE_REGRESSOR",
        10: "BOOSTED_TREE_CLASSIFIER",
        11: "ARIMA",
        12: "AUTOML_REGRESSOR",
        13: "AUTOML_CLASSIFIER",
    }
    Model_ModelType_value = map[string]int32{
        "MODEL_TYPE_UNSPECIFIED":  0,
        "LINEAR_REGRESSION":       1,
        "LOGISTIC_REGRESSION":     2,
        "KMEANS":                  3,
        "MATRIX_FACTORIZATION":    4,
        "DNN_CLASSIFIER":          5,
        "TENSORFLOW":              6,
        "DNN_REGRESSOR":           7,
        "BOOSTED_TREE_REGRESSOR":  9,
        "BOOSTED_TREE_CLASSIFIER": 10,
        "ARIMA":                   11,
        "AUTOML_REGRESSOR":        12,
        "AUTOML_CLASSIFIER":       13,
    }
)

Enum value maps for Model_ModelType.

var (
    Model_LossType_name = map[int32]string{
        0:  "LOSS_TYPE_UNSPECIFIED",
        1:  "MEAN_SQUARED_LOSS",
        2:  "MEAN_LOG_LOSS",
    }
    Model_LossType_value = map[string]int32{
        "LOSS_TYPE_UNSPECIFIED": 0,
        "MEAN_SQUARED_LOSS":     1,
        "MEAN_LOG_LOSS":         2,
    }
)

Enum value maps for Model_LossType.

var (
    Model_DistanceType_name = map[int32]string{
        0:  "DISTANCE_TYPE_UNSPECIFIED",
        1:  "EUCLIDEAN",
        2:  "COSINE",
    }
    Model_DistanceType_value = map[string]int32{
        "DISTANCE_TYPE_UNSPECIFIED": 0,
        "EUCLIDEAN":                 1,
        "COSINE":                    2,
    }
)

Enum value maps for Model_DistanceType.

var (
    Model_DataSplitMethod_name = map[int32]string{
        0:  "DATA_SPLIT_METHOD_UNSPECIFIED",
        1:  "RANDOM",
        2:  "CUSTOM",
        3:  "SEQUENTIAL",
        4:  "NO_SPLIT",
        5:  "AUTO_SPLIT",
    }
    Model_DataSplitMethod_value = map[string]int32{
        "DATA_SPLIT_METHOD_UNSPECIFIED": 0,
        "RANDOM":                        1,
        "CUSTOM":                        2,
        "SEQUENTIAL":                    3,
        "NO_SPLIT":                      4,
        "AUTO_SPLIT":                    5,
    }
)

Enum value maps for Model_DataSplitMethod.

var (
    Model_DataFrequency_name = map[int32]string{
        0:  "DATA_FREQUENCY_UNSPECIFIED",
        1:  "AUTO_FREQUENCY",
        2:  "YEARLY",
        3:  "QUARTERLY",
        4:  "MONTHLY",
        5:  "WEEKLY",
        6:  "DAILY",
        7:  "HOURLY",
    }
    Model_DataFrequency_value = map[string]int32{
        "DATA_FREQUENCY_UNSPECIFIED": 0,
        "AUTO_FREQUENCY":             1,
        "YEARLY":                     2,
        "QUARTERLY":                  3,
        "MONTHLY":                    4,
        "WEEKLY":                     5,
        "DAILY":                      6,
        "HOURLY":                     7,
    }
)

Enum value maps for Model_DataFrequency.

var (
    Model_HolidayRegion_name = map[int32]string{
        0:  "HOLIDAY_REGION_UNSPECIFIED",
        1:  "GLOBAL",
        2:  "NA",
        3:  "JAPAC",
        4:  "EMEA",
        5:  "LAC",
        6:  "AE",
        7:  "AR",
        8:  "AT",
        9:  "AU",
        10: "BE",
        11: "BR",
        12: "CA",
        13: "CH",
        14: "CL",
        15: "CN",
        16: "CO",
        17: "CS",
        18: "CZ",
        19: "DE",
        20: "DK",
        21: "DZ",
        22: "EC",
        23: "EE",
        24: "EG",
        25: "ES",
        26: "FI",
        27: "FR",
        28: "GB",
        29: "GR",
        30: "HK",
        31: "HU",
        32: "ID",
        33: "IE",
        34: "IL",
        35: "IN",
        36: "IR",
        37: "IT",
        38: "JP",
        39: "KR",
        40: "LV",
        41: "MA",
        42: "MX",
        43: "MY",
        44: "NG",
        45: "NL",
        46: "NO",
        47: "NZ",
        48: "PE",
        49: "PH",
        50: "PK",
        51: "PL",
        52: "PT",
        53: "RO",
        54: "RS",
        55: "RU",
        56: "SA",
        57: "SE",
        58: "SG",
        59: "SI",
        60: "SK",
        61: "TH",
        62: "TR",
        63: "TW",
        64: "UA",
        65: "US",
        66: "VE",
        67: "VN",
        68: "ZA",
    }
    Model_HolidayRegion_value = map[string]int32{
        "HOLIDAY_REGION_UNSPECIFIED": 0,
        "GLOBAL":                     1,
        "NA":                         2,
        "JAPAC":                      3,
        "EMEA":                       4,
        "LAC":                        5,
        "AE":                         6,
        "AR":                         7,
        "AT":                         8,
        "AU":                         9,
        "BE":                         10,
        "BR":                         11,
        "CA":                         12,
        "CH":                         13,
        "CL":                         14,
        "CN":                         15,
        "CO":                         16,
        "CS":                         17,
        "CZ":                         18,
        "DE":                         19,
        "DK":                         20,
        "DZ":                         21,
        "EC":                         22,
        "EE":                         23,
        "EG":                         24,
        "ES":                         25,
        "FI":                         26,
        "FR":                         27,
        "GB":                         28,
        "GR":                         29,
        "HK":                         30,
        "HU":                         31,
        "ID":                         32,
        "IE":                         33,
        "IL":                         34,
        "IN":                         35,
        "IR":                         36,
        "IT":                         37,
        "JP":                         38,
        "KR":                         39,
        "LV":                         40,
        "MA":                         41,
        "MX":                         42,
        "MY":                         43,
        "NG":                         44,
        "NL":                         45,
        "NO":                         46,
        "NZ":                         47,
        "PE":                         48,
        "PH":                         49,
        "PK":                         50,
        "PL":                         51,
        "PT":                         52,
        "RO":                         53,
        "RS":                         54,
        "RU":                         55,
        "SA":                         56,
        "SE":                         57,
        "SG":                         58,
        "SI":                         59,
        "SK":                         60,
        "TH":                         61,
        "TR":                         62,
        "TW":                         63,
        "UA":                         64,
        "US":                         65,
        "VE":                         66,
        "VN":                         67,
        "ZA":                         68,
    }
)

Enum value maps for Model_HolidayRegion.

var (
    Model_LearnRateStrategy_name = map[int32]string{
        0:  "LEARN_RATE_STRATEGY_UNSPECIFIED",
        1:  "LINE_SEARCH",
        2:  "CONSTANT",
    }
    Model_LearnRateStrategy_value = map[string]int32{
        "LEARN_RATE_STRATEGY_UNSPECIFIED": 0,
        "LINE_SEARCH":                     1,
        "CONSTANT":                        2,
    }
)

Enum value maps for Model_LearnRateStrategy.

var (
    Model_OptimizationStrategy_name = map[int32]string{
        0:  "OPTIMIZATION_STRATEGY_UNSPECIFIED",
        1:  "BATCH_GRADIENT_DESCENT",
        2:  "NORMAL_EQUATION",
    }
    Model_OptimizationStrategy_value = map[string]int32{
        "OPTIMIZATION_STRATEGY_UNSPECIFIED": 0,
        "BATCH_GRADIENT_DESCENT":            1,
        "NORMAL_EQUATION":                   2,
    }
)

Enum value maps for Model_OptimizationStrategy.

var (
    Model_FeedbackType_name = map[int32]string{
        0:  "FEEDBACK_TYPE_UNSPECIFIED",
        1:  "IMPLICIT",
        2:  "EXPLICIT",
    }
    Model_FeedbackType_value = map[string]int32{
        "FEEDBACK_TYPE_UNSPECIFIED": 0,
        "IMPLICIT":                  1,
        "EXPLICIT":                  2,
    }
)

Enum value maps for Model_FeedbackType.

var (
    Model_SeasonalPeriod_SeasonalPeriodType_name = map[int32]string{
        0:  "SEASONAL_PERIOD_TYPE_UNSPECIFIED",
        1:  "NO_SEASONALITY",
        2:  "DAILY",
        3:  "WEEKLY",
        4:  "MONTHLY",
        5:  "QUARTERLY",
        6:  "YEARLY",
    }
    Model_SeasonalPeriod_SeasonalPeriodType_value = map[string]int32{
        "SEASONAL_PERIOD_TYPE_UNSPECIFIED": 0,
        "NO_SEASONALITY":                   1,
        "DAILY":                            2,
        "WEEKLY":                           3,
        "MONTHLY":                          4,
        "QUARTERLY":                        5,
        "YEARLY":                           6,
    }
)

Enum value maps for Model_SeasonalPeriod_SeasonalPeriodType.

var (
    Model_KmeansEnums_KmeansInitializationMethod_name = map[int32]string{
        0:  "KMEANS_INITIALIZATION_METHOD_UNSPECIFIED",
        1:  "RANDOM",
        2:  "CUSTOM",
        3:  "KMEANS_PLUS_PLUS",
    }
    Model_KmeansEnums_KmeansInitializationMethod_value = map[string]int32{
        "KMEANS_INITIALIZATION_METHOD_UNSPECIFIED": 0,
        "RANDOM":           1,
        "CUSTOM":           2,
        "KMEANS_PLUS_PLUS": 3,
    }
)

Enum value maps for Model_KmeansEnums_KmeansInitializationMethod.

var (
    StandardSqlDataType_TypeKind_name = map[int32]string{
        0:  "TYPE_KIND_UNSPECIFIED",
        2:  "INT64",
        5:  "BOOL",
        7:  "FLOAT64",
        8:  "STRING",
        9:  "BYTES",
        19: "TIMESTAMP",
        10: "DATE",
        20: "TIME",
        21: "DATETIME",
        22: "GEOGRAPHY",
        23: "NUMERIC",
        24: "BIGNUMERIC",
        16: "ARRAY",
        17: "STRUCT",
    }
    StandardSqlDataType_TypeKind_value = map[string]int32{
        "TYPE_KIND_UNSPECIFIED": 0,
        "INT64":                 2,
        "BOOL":                  5,
        "FLOAT64":               7,
        "STRING":                8,
        "BYTES":                 9,
        "TIMESTAMP":             19,
        "DATE":                  10,
        "TIME":                  20,
        "DATETIME":              21,
        "GEOGRAPHY":             22,
        "NUMERIC":               23,
        "BIGNUMERIC":            24,
        "ARRAY":                 16,
        "STRUCT":                17,
    }
)

Enum value maps for StandardSqlDataType_TypeKind.

var File_google_cloud_bigquery_v2_encryption_config_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_model_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_model_reference_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_standard_sql_proto protoreflect.FileDescriptor
var File_google_cloud_bigquery_v2_table_reference_proto protoreflect.FileDescriptor

func RegisterModelServiceServer Uses

func RegisterModelServiceServer(s *grpc.Server, srv ModelServiceServer)

type DeleteModelRequest Uses

type DeleteModelRequest struct {

    // Required. Project ID of the model to delete.
    ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
    // Required. Dataset ID of the model to delete.
    DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
    // Required. Model ID of the model to delete.
    ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
    // contains filtered or unexported fields
}

func (*DeleteModelRequest) Descriptor Uses

func (*DeleteModelRequest) Descriptor() ([]byte, []int)

Deprecated: Use DeleteModelRequest.ProtoReflect.Descriptor instead.

func (*DeleteModelRequest) GetDatasetId Uses

func (x *DeleteModelRequest) GetDatasetId() string

func (*DeleteModelRequest) GetModelId Uses

func (x *DeleteModelRequest) GetModelId() string

func (*DeleteModelRequest) GetProjectId Uses

func (x *DeleteModelRequest) GetProjectId() string

func (*DeleteModelRequest) ProtoMessage Uses

func (*DeleteModelRequest) ProtoMessage()

func (*DeleteModelRequest) ProtoReflect Uses

func (x *DeleteModelRequest) ProtoReflect() protoreflect.Message

func (*DeleteModelRequest) Reset Uses

func (x *DeleteModelRequest) Reset()

func (*DeleteModelRequest) String Uses

func (x *DeleteModelRequest) String() string

type EncryptionConfiguration Uses

type EncryptionConfiguration struct {

    // Optional. Describes the Cloud KMS encryption key that will be used to
    // protect destination BigQuery table. The BigQuery Service Account associated
    // with your project requires access to this encryption key.
    KmsKeyName *wrapperspb.StringValue `protobuf:"bytes,1,opt,name=kms_key_name,json=kmsKeyName,proto3" json:"kms_key_name,omitempty"`
    // contains filtered or unexported fields
}

func (*EncryptionConfiguration) Descriptor Uses

func (*EncryptionConfiguration) Descriptor() ([]byte, []int)

Deprecated: Use EncryptionConfiguration.ProtoReflect.Descriptor instead.

func (*EncryptionConfiguration) GetKmsKeyName Uses

func (x *EncryptionConfiguration) GetKmsKeyName() *wrapperspb.StringValue

func (*EncryptionConfiguration) ProtoMessage Uses

func (*EncryptionConfiguration) ProtoMessage()

func (*EncryptionConfiguration) ProtoReflect Uses

func (x *EncryptionConfiguration) ProtoReflect() protoreflect.Message

func (*EncryptionConfiguration) Reset Uses

func (x *EncryptionConfiguration) Reset()

func (*EncryptionConfiguration) String Uses

func (x *EncryptionConfiguration) String() string

type GetModelRequest Uses

type GetModelRequest struct {

    // Required. Project ID of the requested model.
    ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
    // Required. Dataset ID of the requested model.
    DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
    // Required. Model ID of the requested model.
    ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
    // contains filtered or unexported fields
}

func (*GetModelRequest) Descriptor Uses

func (*GetModelRequest) Descriptor() ([]byte, []int)

Deprecated: Use GetModelRequest.ProtoReflect.Descriptor instead.

func (*GetModelRequest) GetDatasetId Uses

func (x *GetModelRequest) GetDatasetId() string

func (*GetModelRequest) GetModelId Uses

func (x *GetModelRequest) GetModelId() string

func (*GetModelRequest) GetProjectId Uses

func (x *GetModelRequest) GetProjectId() string

func (*GetModelRequest) ProtoMessage Uses

func (*GetModelRequest) ProtoMessage()

func (*GetModelRequest) ProtoReflect Uses

func (x *GetModelRequest) ProtoReflect() protoreflect.Message

func (*GetModelRequest) Reset Uses

func (x *GetModelRequest) Reset()

func (*GetModelRequest) String Uses

func (x *GetModelRequest) String() string

type ListModelsRequest Uses

type ListModelsRequest struct {

    // Required. Project ID of the models to list.
    ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
    // Required. Dataset ID of the models to list.
    DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
    // The maximum number of results to return in a single response page.
    // Leverage the page tokens to iterate through the entire collection.
    MaxResults *wrapperspb.UInt32Value `protobuf:"bytes,3,opt,name=max_results,json=maxResults,proto3" json:"max_results,omitempty"`
    // Page token, returned by a previous call to request the next page of
    // results
    PageToken string `protobuf:"bytes,4,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
    // contains filtered or unexported fields
}

func (*ListModelsRequest) Descriptor Uses

func (*ListModelsRequest) Descriptor() ([]byte, []int)

Deprecated: Use ListModelsRequest.ProtoReflect.Descriptor instead.

func (*ListModelsRequest) GetDatasetId Uses

func (x *ListModelsRequest) GetDatasetId() string

func (*ListModelsRequest) GetMaxResults Uses

func (x *ListModelsRequest) GetMaxResults() *wrapperspb.UInt32Value

func (*ListModelsRequest) GetPageToken Uses

func (x *ListModelsRequest) GetPageToken() string

func (*ListModelsRequest) GetProjectId Uses

func (x *ListModelsRequest) GetProjectId() string

func (*ListModelsRequest) ProtoMessage Uses

func (*ListModelsRequest) ProtoMessage()

func (*ListModelsRequest) ProtoReflect Uses

func (x *ListModelsRequest) ProtoReflect() protoreflect.Message

func (*ListModelsRequest) Reset Uses

func (x *ListModelsRequest) Reset()

func (*ListModelsRequest) String Uses

func (x *ListModelsRequest) String() string

type ListModelsResponse Uses

type ListModelsResponse struct {

    // Models in the requested dataset. Only the following fields are populated:
    // model_reference, model_type, creation_time, last_modified_time and
    // labels.
    Models []*Model `protobuf:"bytes,1,rep,name=models,proto3" json:"models,omitempty"`
    // A token to request the next page of results.
    NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
    // contains filtered or unexported fields
}

func (*ListModelsResponse) Descriptor Uses

func (*ListModelsResponse) Descriptor() ([]byte, []int)

Deprecated: Use ListModelsResponse.ProtoReflect.Descriptor instead.

func (*ListModelsResponse) GetModels Uses

func (x *ListModelsResponse) GetModels() []*Model

func (*ListModelsResponse) GetNextPageToken Uses

func (x *ListModelsResponse) GetNextPageToken() string

func (*ListModelsResponse) ProtoMessage Uses

func (*ListModelsResponse) ProtoMessage()

func (*ListModelsResponse) ProtoReflect Uses

func (x *ListModelsResponse) ProtoReflect() protoreflect.Message

func (*ListModelsResponse) Reset Uses

func (x *ListModelsResponse) Reset()

func (*ListModelsResponse) String Uses

func (x *ListModelsResponse) String() string

type Model Uses

type Model struct {

    // Output only. A hash of this resource.
    Etag string `protobuf:"bytes,1,opt,name=etag,proto3" json:"etag,omitempty"`
    // Required. Unique identifier for this model.
    ModelReference *ModelReference `protobuf:"bytes,2,opt,name=model_reference,json=modelReference,proto3" json:"model_reference,omitempty"`
    // Output only. The time when this model was created, in millisecs since the epoch.
    CreationTime int64 `protobuf:"varint,5,opt,name=creation_time,json=creationTime,proto3" json:"creation_time,omitempty"`
    // Output only. The time when this model was last modified, in millisecs since the epoch.
    LastModifiedTime int64 `protobuf:"varint,6,opt,name=last_modified_time,json=lastModifiedTime,proto3" json:"last_modified_time,omitempty"`
    // Optional. A user-friendly description of this model.
    Description string `protobuf:"bytes,12,opt,name=description,proto3" json:"description,omitempty"`
    // Optional. A descriptive name for this model.
    FriendlyName string `protobuf:"bytes,14,opt,name=friendly_name,json=friendlyName,proto3" json:"friendly_name,omitempty"`
    // The labels associated with this model. You can use these to organize
    // and group your models. Label keys and values can be no longer
    // than 63 characters, can only contain lowercase letters, numeric
    // characters, underscores and dashes. International characters are allowed.
    // Label values are optional. Label keys must start with a letter and each
    // label in the list must have a different key.
    Labels map[string]string `protobuf:"bytes,15,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
    // Optional. The time when this model expires, in milliseconds since the epoch.
    // If not present, the model will persist indefinitely. Expired models
    // will be deleted and their storage reclaimed.  The defaultTableExpirationMs
    // property of the encapsulating dataset can be used to set a default
    // expirationTime on newly created models.
    ExpirationTime int64 `protobuf:"varint,16,opt,name=expiration_time,json=expirationTime,proto3" json:"expiration_time,omitempty"`
    // Output only. The geographic location where the model resides. This value
    // is inherited from the dataset.
    Location string `protobuf:"bytes,13,opt,name=location,proto3" json:"location,omitempty"`
    // Custom encryption configuration (e.g., Cloud KMS keys). This shows the
    // encryption configuration of the model data while stored in BigQuery
    // storage. This field can be used with PatchModel to update encryption key
    // for an already encrypted model.
    EncryptionConfiguration *EncryptionConfiguration `protobuf:"bytes,17,opt,name=encryption_configuration,json=encryptionConfiguration,proto3" json:"encryption_configuration,omitempty"`
    // Output only. Type of the model resource.
    ModelType Model_ModelType `protobuf:"varint,7,opt,name=model_type,json=modelType,proto3,enum=google.cloud.bigquery.v2.Model_ModelType" json:"model_type,omitempty"`
    // Output only. Information for all training runs in increasing order of start_time.
    TrainingRuns []*Model_TrainingRun `protobuf:"bytes,9,rep,name=training_runs,json=trainingRuns,proto3" json:"training_runs,omitempty"`
    // Output only. Input feature columns that were used to train this model.
    FeatureColumns []*StandardSqlField `protobuf:"bytes,10,rep,name=feature_columns,json=featureColumns,proto3" json:"feature_columns,omitempty"`
    // Output only. Label columns that were used to train this model.
    // The output of the model will have a "predicted_" prefix to these columns.
    LabelColumns []*StandardSqlField `protobuf:"bytes,11,rep,name=label_columns,json=labelColumns,proto3" json:"label_columns,omitempty"`
    // contains filtered or unexported fields
}

func (*Model) Descriptor Uses

func (*Model) Descriptor() ([]byte, []int)

Deprecated: Use Model.ProtoReflect.Descriptor instead.

func (*Model) GetCreationTime Uses

func (x *Model) GetCreationTime() int64

func (*Model) GetDescription Uses

func (x *Model) GetDescription() string

func (*Model) GetEncryptionConfiguration Uses

func (x *Model) GetEncryptionConfiguration() *EncryptionConfiguration

func (*Model) GetEtag Uses

func (x *Model) GetEtag() string

func (*Model) GetExpirationTime Uses

func (x *Model) GetExpirationTime() int64

func (*Model) GetFeatureColumns Uses

func (x *Model) GetFeatureColumns() []*StandardSqlField

func (*Model) GetFriendlyName Uses

func (x *Model) GetFriendlyName() string

func (*Model) GetLabelColumns Uses

func (x *Model) GetLabelColumns() []*StandardSqlField

func (*Model) GetLabels Uses

func (x *Model) GetLabels() map[string]string

func (*Model) GetLastModifiedTime Uses

func (x *Model) GetLastModifiedTime() int64

func (*Model) GetLocation Uses

func (x *Model) GetLocation() string

func (*Model) GetModelReference Uses

func (x *Model) GetModelReference() *ModelReference

func (*Model) GetModelType Uses

func (x *Model) GetModelType() Model_ModelType

func (*Model) GetTrainingRuns Uses

func (x *Model) GetTrainingRuns() []*Model_TrainingRun

func (*Model) ProtoMessage Uses

func (*Model) ProtoMessage()

func (*Model) ProtoReflect Uses

func (x *Model) ProtoReflect() protoreflect.Message

func (*Model) Reset Uses

func (x *Model) Reset()

func (*Model) String Uses

func (x *Model) String() string

type ModelReference Uses

type ModelReference struct {

    // Required. The ID of the project containing this model.
    ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
    // Required. The ID of the dataset containing this model.
    DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
    // Required. The ID of the model. The ID must contain only
    // letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum
    // length is 1,024 characters.
    ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
    // contains filtered or unexported fields
}

Id path of a model.

func (*ModelReference) Descriptor Uses

func (*ModelReference) Descriptor() ([]byte, []int)

Deprecated: Use ModelReference.ProtoReflect.Descriptor instead.

func (*ModelReference) GetDatasetId Uses

func (x *ModelReference) GetDatasetId() string

func (*ModelReference) GetModelId Uses

func (x *ModelReference) GetModelId() string

func (*ModelReference) GetProjectId Uses

func (x *ModelReference) GetProjectId() string

func (*ModelReference) ProtoMessage Uses

func (*ModelReference) ProtoMessage()

func (*ModelReference) ProtoReflect Uses

func (x *ModelReference) ProtoReflect() protoreflect.Message

func (*ModelReference) Reset Uses

func (x *ModelReference) Reset()

func (*ModelReference) String Uses

func (x *ModelReference) String() string

type ModelServiceClient Uses

type ModelServiceClient interface {
    // Gets the specified model resource by model ID.
    GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error)
    // Lists all models in the specified dataset. Requires the READER dataset
    // role.
    ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error)
    // Patch specific fields in the specified model.
    PatchModel(ctx context.Context, in *PatchModelRequest, opts ...grpc.CallOption) (*Model, error)
    // Deletes the model specified by modelId from the dataset.
    DeleteModel(ctx context.Context, in *DeleteModelRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
}

ModelServiceClient is the client API for ModelService service.

For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.

func NewModelServiceClient Uses

func NewModelServiceClient(cc grpc.ClientConnInterface) ModelServiceClient

type ModelServiceServer Uses

type ModelServiceServer interface {
    // Gets the specified model resource by model ID.
    GetModel(context.Context, *GetModelRequest) (*Model, error)
    // Lists all models in the specified dataset. Requires the READER dataset
    // role.
    ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)
    // Patch specific fields in the specified model.
    PatchModel(context.Context, *PatchModelRequest) (*Model, error)
    // Deletes the model specified by modelId from the dataset.
    DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error)
}

ModelServiceServer is the server API for ModelService service.

type Model_AggregateClassificationMetrics Uses

type Model_AggregateClassificationMetrics struct {

    // Precision is the fraction of actual positive predictions that had
    // positive actual labels. For multiclass this is a macro-averaged
    // metric treating each class as a binary classifier.
    Precision *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=precision,proto3" json:"precision,omitempty"`
    // Recall is the fraction of actual positive labels that were given a
    // positive prediction. For multiclass this is a macro-averaged metric.
    Recall *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=recall,proto3" json:"recall,omitempty"`
    // Accuracy is the fraction of predictions given the correct label. For
    // multiclass this is a micro-averaged metric.
    Accuracy *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=accuracy,proto3" json:"accuracy,omitempty"`
    // Threshold at which the metrics are computed. For binary
    // classification models this is the positive class threshold.
    // For multi-class classfication models this is the confidence
    // threshold.
    Threshold *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=threshold,proto3" json:"threshold,omitempty"`
    // The F1 score is an average of recall and precision. For multiclass
    // this is a macro-averaged metric.
    F1Score *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"`
    // Logarithmic Loss. For multiclass this is a macro-averaged metric.
    LogLoss *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=log_loss,json=logLoss,proto3" json:"log_loss,omitempty"`
    // Area Under a ROC Curve. For multiclass this is a macro-averaged
    // metric.
    RocAuc *wrapperspb.DoubleValue `protobuf:"bytes,7,opt,name=roc_auc,json=rocAuc,proto3" json:"roc_auc,omitempty"`
    // contains filtered or unexported fields
}

Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows.

func (*Model_AggregateClassificationMetrics) Descriptor Uses

func (*Model_AggregateClassificationMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_AggregateClassificationMetrics.ProtoReflect.Descriptor instead.

func (*Model_AggregateClassificationMetrics) GetAccuracy Uses

func (x *Model_AggregateClassificationMetrics) GetAccuracy() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) GetF1Score Uses

func (x *Model_AggregateClassificationMetrics) GetF1Score() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) GetLogLoss Uses

func (x *Model_AggregateClassificationMetrics) GetLogLoss() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) GetPrecision Uses

func (x *Model_AggregateClassificationMetrics) GetPrecision() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) GetRecall Uses

func (x *Model_AggregateClassificationMetrics) GetRecall() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) GetRocAuc Uses

func (x *Model_AggregateClassificationMetrics) GetRocAuc() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) GetThreshold Uses

func (x *Model_AggregateClassificationMetrics) GetThreshold() *wrapperspb.DoubleValue

func (*Model_AggregateClassificationMetrics) ProtoMessage Uses

func (*Model_AggregateClassificationMetrics) ProtoMessage()

func (*Model_AggregateClassificationMetrics) ProtoReflect Uses

func (x *Model_AggregateClassificationMetrics) ProtoReflect() protoreflect.Message

func (*Model_AggregateClassificationMetrics) Reset Uses

func (x *Model_AggregateClassificationMetrics) Reset()

func (*Model_AggregateClassificationMetrics) String Uses

func (x *Model_AggregateClassificationMetrics) String() string

type Model_ArimaFittingMetrics Uses

type Model_ArimaFittingMetrics struct {

    // Log-likelihood.
    LogLikelihood float64 `protobuf:"fixed64,1,opt,name=log_likelihood,json=logLikelihood,proto3" json:"log_likelihood,omitempty"`
    // AIC.
    Aic float64 `protobuf:"fixed64,2,opt,name=aic,proto3" json:"aic,omitempty"`
    // Variance.
    Variance float64 `protobuf:"fixed64,3,opt,name=variance,proto3" json:"variance,omitempty"`
    // contains filtered or unexported fields
}

ARIMA model fitting metrics.

func (*Model_ArimaFittingMetrics) Descriptor Uses

func (*Model_ArimaFittingMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_ArimaFittingMetrics.ProtoReflect.Descriptor instead.

func (*Model_ArimaFittingMetrics) GetAic Uses

func (x *Model_ArimaFittingMetrics) GetAic() float64

func (*Model_ArimaFittingMetrics) GetLogLikelihood Uses

func (x *Model_ArimaFittingMetrics) GetLogLikelihood() float64

func (*Model_ArimaFittingMetrics) GetVariance Uses

func (x *Model_ArimaFittingMetrics) GetVariance() float64

func (*Model_ArimaFittingMetrics) ProtoMessage Uses

func (*Model_ArimaFittingMetrics) ProtoMessage()

func (*Model_ArimaFittingMetrics) ProtoReflect Uses

func (x *Model_ArimaFittingMetrics) ProtoReflect() protoreflect.Message

func (*Model_ArimaFittingMetrics) Reset Uses

func (x *Model_ArimaFittingMetrics) Reset()

func (*Model_ArimaFittingMetrics) String Uses

func (x *Model_ArimaFittingMetrics) String() string

type Model_ArimaForecastingMetrics Uses

type Model_ArimaForecastingMetrics struct {

    // Non-seasonal order.
    NonSeasonalOrder []*Model_ArimaOrder `protobuf:"bytes,1,rep,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
    // Arima model fitting metrics.
    ArimaFittingMetrics []*Model_ArimaFittingMetrics `protobuf:"bytes,2,rep,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"`
    // Seasonal periods. Repeated because multiple periods are supported for one
    // time series.
    SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,3,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
    // Whether Arima model fitted with drift or not. It is always false when d
    // is not 1.
    HasDrift []bool `protobuf:"varint,4,rep,packed,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"`
    // Id to differentiate different time series for the large-scale case.
    TimeSeriesId []string `protobuf:"bytes,5,rep,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"`
    // Repeated as there can be many metric sets (one for each model) in
    // auto-arima and the large-scale case.
    ArimaSingleModelForecastingMetrics []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics `protobuf:"bytes,6,rep,name=arima_single_model_forecasting_metrics,json=arimaSingleModelForecastingMetrics,proto3" json:"arima_single_model_forecasting_metrics,omitempty"`
    // contains filtered or unexported fields
}

Model evaluation metrics for ARIMA forecasting models.

func (*Model_ArimaForecastingMetrics) Descriptor Uses

func (*Model_ArimaForecastingMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_ArimaForecastingMetrics.ProtoReflect.Descriptor instead.

func (*Model_ArimaForecastingMetrics) GetArimaFittingMetrics Uses

func (x *Model_ArimaForecastingMetrics) GetArimaFittingMetrics() []*Model_ArimaFittingMetrics

func (*Model_ArimaForecastingMetrics) GetArimaSingleModelForecastingMetrics Uses

func (x *Model_ArimaForecastingMetrics) GetArimaSingleModelForecastingMetrics() []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics

func (*Model_ArimaForecastingMetrics) GetHasDrift Uses

func (x *Model_ArimaForecastingMetrics) GetHasDrift() []bool

func (*Model_ArimaForecastingMetrics) GetNonSeasonalOrder Uses

func (x *Model_ArimaForecastingMetrics) GetNonSeasonalOrder() []*Model_ArimaOrder

func (*Model_ArimaForecastingMetrics) GetSeasonalPeriods Uses

func (x *Model_ArimaForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType

func (*Model_ArimaForecastingMetrics) GetTimeSeriesId Uses

func (x *Model_ArimaForecastingMetrics) GetTimeSeriesId() []string

func (*Model_ArimaForecastingMetrics) ProtoMessage Uses

func (*Model_ArimaForecastingMetrics) ProtoMessage()

func (*Model_ArimaForecastingMetrics) ProtoReflect Uses

func (x *Model_ArimaForecastingMetrics) ProtoReflect() protoreflect.Message

func (*Model_ArimaForecastingMetrics) Reset Uses

func (x *Model_ArimaForecastingMetrics) Reset()

func (*Model_ArimaForecastingMetrics) String Uses

func (x *Model_ArimaForecastingMetrics) String() string

type Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics Uses

type Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics struct {

    // Non-seasonal order.
    NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,1,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
    // Arima fitting metrics.
    ArimaFittingMetrics *Model_ArimaFittingMetrics `protobuf:"bytes,2,opt,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"`
    // Is arima model fitted with drift or not. It is always false when d
    // is not 1.
    HasDrift bool `protobuf:"varint,3,opt,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"`
    // The id to indicate different time series.
    TimeSeriesId string `protobuf:"bytes,4,opt,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"`
    // Seasonal periods. Repeated because multiple periods are supported
    // for one time series.
    SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,5,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
    // contains filtered or unexported fields
}

Model evaluation metrics for a single ARIMA forecasting model.

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Descriptor Uses

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics.ProtoReflect.Descriptor instead.

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetArimaFittingMetrics Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetArimaFittingMetrics() *Model_ArimaFittingMetrics

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasDrift Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasDrift() bool

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetNonSeasonalOrder Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetNonSeasonalOrder() *Model_ArimaOrder

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetSeasonalPeriods Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesId Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesId() string

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoMessage Uses

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoMessage()

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoReflect Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoReflect() protoreflect.Message

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Reset Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Reset()

func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) String Uses

func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) String() string

type Model_ArimaOrder Uses

type Model_ArimaOrder struct {

    // Order of the autoregressive part.
    P   int64 `protobuf:"varint,1,opt,name=p,proto3" json:"p,omitempty"`
    // Order of the differencing part.
    D   int64 `protobuf:"varint,2,opt,name=d,proto3" json:"d,omitempty"`
    // Order of the moving-average part.
    Q   int64 `protobuf:"varint,3,opt,name=q,proto3" json:"q,omitempty"`
    // contains filtered or unexported fields
}

Arima order, can be used for both non-seasonal and seasonal parts.

func (*Model_ArimaOrder) Descriptor Uses

func (*Model_ArimaOrder) Descriptor() ([]byte, []int)

Deprecated: Use Model_ArimaOrder.ProtoReflect.Descriptor instead.

func (*Model_ArimaOrder) GetD Uses

func (x *Model_ArimaOrder) GetD() int64

func (*Model_ArimaOrder) GetP Uses

func (x *Model_ArimaOrder) GetP() int64

func (*Model_ArimaOrder) GetQ Uses

func (x *Model_ArimaOrder) GetQ() int64

func (*Model_ArimaOrder) ProtoMessage Uses

func (*Model_ArimaOrder) ProtoMessage()

func (*Model_ArimaOrder) ProtoReflect Uses

func (x *Model_ArimaOrder) ProtoReflect() protoreflect.Message

func (*Model_ArimaOrder) Reset Uses

func (x *Model_ArimaOrder) Reset()

func (*Model_ArimaOrder) String Uses

func (x *Model_ArimaOrder) String() string

type Model_BinaryClassificationMetrics Uses

type Model_BinaryClassificationMetrics struct {

    // Aggregate classification metrics.
    AggregateClassificationMetrics *Model_AggregateClassificationMetrics `protobuf:"bytes,1,opt,name=aggregate_classification_metrics,json=aggregateClassificationMetrics,proto3" json:"aggregate_classification_metrics,omitempty"`
    // Binary confusion matrix at multiple thresholds.
    BinaryConfusionMatrixList []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix `protobuf:"bytes,2,rep,name=binary_confusion_matrix_list,json=binaryConfusionMatrixList,proto3" json:"binary_confusion_matrix_list,omitempty"`
    // Label representing the positive class.
    PositiveLabel string `protobuf:"bytes,3,opt,name=positive_label,json=positiveLabel,proto3" json:"positive_label,omitempty"`
    // Label representing the negative class.
    NegativeLabel string `protobuf:"bytes,4,opt,name=negative_label,json=negativeLabel,proto3" json:"negative_label,omitempty"`
    // contains filtered or unexported fields
}

Evaluation metrics for binary classification/classifier models.

func (*Model_BinaryClassificationMetrics) Descriptor Uses

func (*Model_BinaryClassificationMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_BinaryClassificationMetrics.ProtoReflect.Descriptor instead.

func (*Model_BinaryClassificationMetrics) GetAggregateClassificationMetrics Uses

func (x *Model_BinaryClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics

func (*Model_BinaryClassificationMetrics) GetBinaryConfusionMatrixList Uses

func (x *Model_BinaryClassificationMetrics) GetBinaryConfusionMatrixList() []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix

func (*Model_BinaryClassificationMetrics) GetNegativeLabel Uses

func (x *Model_BinaryClassificationMetrics) GetNegativeLabel() string

func (*Model_BinaryClassificationMetrics) GetPositiveLabel Uses

func (x *Model_BinaryClassificationMetrics) GetPositiveLabel() string

func (*Model_BinaryClassificationMetrics) ProtoMessage Uses

func (*Model_BinaryClassificationMetrics) ProtoMessage()

func (*Model_BinaryClassificationMetrics) ProtoReflect Uses

func (x *Model_BinaryClassificationMetrics) ProtoReflect() protoreflect.Message

func (*Model_BinaryClassificationMetrics) Reset Uses

func (x *Model_BinaryClassificationMetrics) Reset()

func (*Model_BinaryClassificationMetrics) String Uses

func (x *Model_BinaryClassificationMetrics) String() string

type Model_BinaryClassificationMetrics_BinaryConfusionMatrix Uses

type Model_BinaryClassificationMetrics_BinaryConfusionMatrix struct {

    // Threshold value used when computing each of the following metric.
    PositiveClassThreshold *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=positive_class_threshold,json=positiveClassThreshold,proto3" json:"positive_class_threshold,omitempty"`
    // Number of true samples predicted as true.
    TruePositives *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=true_positives,json=truePositives,proto3" json:"true_positives,omitempty"`
    // Number of false samples predicted as true.
    FalsePositives *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=false_positives,json=falsePositives,proto3" json:"false_positives,omitempty"`
    // Number of true samples predicted as false.
    TrueNegatives *wrapperspb.Int64Value `protobuf:"bytes,4,opt,name=true_negatives,json=trueNegatives,proto3" json:"true_negatives,omitempty"`
    // Number of false samples predicted as false.
    FalseNegatives *wrapperspb.Int64Value `protobuf:"bytes,5,opt,name=false_negatives,json=falseNegatives,proto3" json:"false_negatives,omitempty"`
    // The fraction of actual positive predictions that had positive actual
    // labels.
    Precision *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=precision,proto3" json:"precision,omitempty"`
    // The fraction of actual positive labels that were given a positive
    // prediction.
    Recall *wrapperspb.DoubleValue `protobuf:"bytes,7,opt,name=recall,proto3" json:"recall,omitempty"`
    // The equally weighted average of recall and precision.
    F1Score *wrapperspb.DoubleValue `protobuf:"bytes,8,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"`
    // The fraction of predictions given the correct label.
    Accuracy *wrapperspb.DoubleValue `protobuf:"bytes,9,opt,name=accuracy,proto3" json:"accuracy,omitempty"`
    // contains filtered or unexported fields
}

Confusion matrix for binary classification models.

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Descriptor Uses

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Descriptor() ([]byte, []int)

Deprecated: Use Model_BinaryClassificationMetrics_BinaryConfusionMatrix.ProtoReflect.Descriptor instead.

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetAccuracy Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetAccuracy() *wrapperspb.DoubleValue

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetF1Score Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetF1Score() *wrapperspb.DoubleValue

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalseNegatives Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalseNegatives() *wrapperspb.Int64Value

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalsePositives Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalsePositives() *wrapperspb.Int64Value

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPositiveClassThreshold Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPositiveClassThreshold() *wrapperspb.DoubleValue

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPrecision Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPrecision() *wrapperspb.DoubleValue

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetRecall Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetRecall() *wrapperspb.DoubleValue

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTrueNegatives Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTrueNegatives() *wrapperspb.Int64Value

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTruePositives Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTruePositives() *wrapperspb.Int64Value

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoMessage Uses

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoMessage()

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoReflect Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoReflect() protoreflect.Message

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Reset Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Reset()

func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) String Uses

func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) String() string

type Model_ClusteringMetrics Uses

type Model_ClusteringMetrics struct {

    // Davies-Bouldin index.
    DaviesBouldinIndex *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=davies_bouldin_index,json=daviesBouldinIndex,proto3" json:"davies_bouldin_index,omitempty"`
    // Mean of squared distances between each sample to its cluster centroid.
    MeanSquaredDistance *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_distance,json=meanSquaredDistance,proto3" json:"mean_squared_distance,omitempty"`
    // [Beta] Information for all clusters.
    Clusters []*Model_ClusteringMetrics_Cluster `protobuf:"bytes,3,rep,name=clusters,proto3" json:"clusters,omitempty"`
    // contains filtered or unexported fields
}

Evaluation metrics for clustering models.

func (*Model_ClusteringMetrics) Descriptor Uses

func (*Model_ClusteringMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_ClusteringMetrics.ProtoReflect.Descriptor instead.

func (*Model_ClusteringMetrics) GetClusters Uses

func (x *Model_ClusteringMetrics) GetClusters() []*Model_ClusteringMetrics_Cluster

func (*Model_ClusteringMetrics) GetDaviesBouldinIndex Uses

func (x *Model_ClusteringMetrics) GetDaviesBouldinIndex() *wrapperspb.DoubleValue

func (*Model_ClusteringMetrics) GetMeanSquaredDistance Uses

func (x *Model_ClusteringMetrics) GetMeanSquaredDistance() *wrapperspb.DoubleValue

func (*Model_ClusteringMetrics) ProtoMessage Uses

func (*Model_ClusteringMetrics) ProtoMessage()

func (*Model_ClusteringMetrics) ProtoReflect Uses

func (x *Model_ClusteringMetrics) ProtoReflect() protoreflect.Message

func (*Model_ClusteringMetrics) Reset Uses

func (x *Model_ClusteringMetrics) Reset()

func (*Model_ClusteringMetrics) String Uses

func (x *Model_ClusteringMetrics) String() string

type Model_ClusteringMetrics_Cluster Uses

type Model_ClusteringMetrics_Cluster struct {

    // Centroid id.
    CentroidId int64 `protobuf:"varint,1,opt,name=centroid_id,json=centroidId,proto3" json:"centroid_id,omitempty"`
    // Values of highly variant features for this cluster.
    FeatureValues []*Model_ClusteringMetrics_Cluster_FeatureValue `protobuf:"bytes,2,rep,name=feature_values,json=featureValues,proto3" json:"feature_values,omitempty"`
    // Count of training data rows that were assigned to this cluster.
    Count *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=count,proto3" json:"count,omitempty"`
    // contains filtered or unexported fields
}

Message containing the information about one cluster.

func (*Model_ClusteringMetrics_Cluster) Descriptor Uses

func (*Model_ClusteringMetrics_Cluster) Descriptor() ([]byte, []int)

Deprecated: Use Model_ClusteringMetrics_Cluster.ProtoReflect.Descriptor instead.

func (*Model_ClusteringMetrics_Cluster) GetCentroidId Uses

func (x *Model_ClusteringMetrics_Cluster) GetCentroidId() int64

func (*Model_ClusteringMetrics_Cluster) GetCount Uses

func (x *Model_ClusteringMetrics_Cluster) GetCount() *wrapperspb.Int64Value

func (*Model_ClusteringMetrics_Cluster) GetFeatureValues Uses

func (x *Model_ClusteringMetrics_Cluster) GetFeatureValues() []*Model_ClusteringMetrics_Cluster_FeatureValue

func (*Model_ClusteringMetrics_Cluster) ProtoMessage Uses

func (*Model_ClusteringMetrics_Cluster) ProtoMessage()

func (*Model_ClusteringMetrics_Cluster) ProtoReflect Uses

func (x *Model_ClusteringMetrics_Cluster) ProtoReflect() protoreflect.Message

func (*Model_ClusteringMetrics_Cluster) Reset Uses

func (x *Model_ClusteringMetrics_Cluster) Reset()

func (*Model_ClusteringMetrics_Cluster) String Uses

func (x *Model_ClusteringMetrics_Cluster) String() string

type Model_ClusteringMetrics_Cluster_FeatureValue Uses

type Model_ClusteringMetrics_Cluster_FeatureValue struct {

    // The feature column name.
    FeatureColumn string `protobuf:"bytes,1,opt,name=feature_column,json=featureColumn,proto3" json:"feature_column,omitempty"`
    // Types that are assignable to Value:
    //	*Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue
    //	*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_
    Value isModel_ClusteringMetrics_Cluster_FeatureValue_Value `protobuf_oneof:"value"`
    // contains filtered or unexported fields
}

Representative value of a single feature within the cluster.

func (*Model_ClusteringMetrics_Cluster_FeatureValue) Descriptor Uses

func (*Model_ClusteringMetrics_Cluster_FeatureValue) Descriptor() ([]byte, []int)

Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue.ProtoReflect.Descriptor instead.

func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetCategoricalValue Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetCategoricalValue() *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue

func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetFeatureColumn Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetFeatureColumn() string

func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetNumericalValue Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetNumericalValue() *wrapperspb.DoubleValue

func (*Model_ClusteringMetrics_Cluster_FeatureValue) GetValue Uses

func (m *Model_ClusteringMetrics_Cluster_FeatureValue) GetValue() isModel_ClusteringMetrics_Cluster_FeatureValue_Value

func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoMessage Uses

func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoMessage()

func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoReflect Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue) ProtoReflect() protoreflect.Message

func (*Model_ClusteringMetrics_Cluster_FeatureValue) Reset Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue) Reset()

func (*Model_ClusteringMetrics_Cluster_FeatureValue) String Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue) String() string

type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue Uses

type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue struct {

    // Counts of all categories for the categorical feature. If there are
    // more than ten categories, we return top ten (by count) and return
    // one more CategoryCount with category "_OTHER_" and count as
    // aggregate counts of remaining categories.
    CategoryCounts []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount `protobuf:"bytes,1,rep,name=category_counts,json=categoryCounts,proto3" json:"category_counts,omitempty"`
    // contains filtered or unexported fields
}

Representative value of a categorical feature.

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Descriptor Uses

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Descriptor() ([]byte, []int)

Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue.ProtoReflect.Descriptor instead.

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) GetCategoryCounts Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) GetCategoryCounts() []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoMessage Uses

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoMessage()

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoReflect Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoReflect() protoreflect.Message

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Reset Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Reset()

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) String Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) String() string

type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_ Uses

type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_ struct {
    // The categorical feature value.
    CategoricalValue *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue `protobuf:"bytes,3,opt,name=categorical_value,json=categoricalValue,proto3,oneof"`
}

type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount Uses

type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount struct {

    // The name of category.
    Category string `protobuf:"bytes,1,opt,name=category,proto3" json:"category,omitempty"`
    // The count of training samples matching the category within the
    // cluster.
    Count *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=count,proto3" json:"count,omitempty"`
    // contains filtered or unexported fields
}

Represents the count of a single category within the cluster.

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Descriptor Uses

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Descriptor() ([]byte, []int)

Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount.ProtoReflect.Descriptor instead.

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCategory Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCategory() string

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCount Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCount() *wrapperspb.Int64Value

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoMessage Uses

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoMessage()

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoReflect Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoReflect() protoreflect.Message

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Reset Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Reset()

func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) String Uses

func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) String() string

type Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue Uses

type Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue struct {
    // The numerical feature value. This is the centroid value for this
    // feature.
    NumericalValue *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=numerical_value,json=numericalValue,proto3,oneof"`
}

type Model_DataFrequency Uses

type Model_DataFrequency int32

Type of supported data frequency for time series forecasting models.

const (
    Model_DATA_FREQUENCY_UNSPECIFIED Model_DataFrequency = 0
    // Automatically inferred from timestamps.
    Model_AUTO_FREQUENCY Model_DataFrequency = 1
    // Yearly data.
    Model_YEARLY Model_DataFrequency = 2
    // Quarterly data.
    Model_QUARTERLY Model_DataFrequency = 3
    // Monthly data.
    Model_MONTHLY Model_DataFrequency = 4
    // Weekly data.
    Model_WEEKLY Model_DataFrequency = 5
    // Daily data.
    Model_DAILY Model_DataFrequency = 6
    // Hourly data.
    Model_HOURLY Model_DataFrequency = 7
)

func (Model_DataFrequency) Descriptor Uses

func (Model_DataFrequency) Descriptor() protoreflect.EnumDescriptor

func (Model_DataFrequency) Enum Uses

func (x Model_DataFrequency) Enum() *Model_DataFrequency

func (Model_DataFrequency) EnumDescriptor Uses

func (Model_DataFrequency) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_DataFrequency.Descriptor instead.

func (Model_DataFrequency) Number Uses

func (x Model_DataFrequency) Number() protoreflect.EnumNumber

func (Model_DataFrequency) String Uses

func (x Model_DataFrequency) String() string

func (Model_DataFrequency) Type Uses

func (Model_DataFrequency) Type() protoreflect.EnumType

type Model_DataSplitMethod Uses

type Model_DataSplitMethod int32

Indicates the method to split input data into multiple tables.

const (
    Model_DATA_SPLIT_METHOD_UNSPECIFIED Model_DataSplitMethod = 0
    // Splits data randomly.
    Model_RANDOM Model_DataSplitMethod = 1
    // Splits data with the user provided tags.
    Model_CUSTOM Model_DataSplitMethod = 2
    // Splits data sequentially.
    Model_SEQUENTIAL Model_DataSplitMethod = 3
    // Data split will be skipped.
    Model_NO_SPLIT Model_DataSplitMethod = 4
    // Splits data automatically: Uses NO_SPLIT if the data size is small.
    // Otherwise uses RANDOM.
    Model_AUTO_SPLIT Model_DataSplitMethod = 5
)

func (Model_DataSplitMethod) Descriptor Uses

func (Model_DataSplitMethod) Descriptor() protoreflect.EnumDescriptor

func (Model_DataSplitMethod) Enum Uses

func (x Model_DataSplitMethod) Enum() *Model_DataSplitMethod

func (Model_DataSplitMethod) EnumDescriptor Uses

func (Model_DataSplitMethod) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_DataSplitMethod.Descriptor instead.

func (Model_DataSplitMethod) Number Uses

func (x Model_DataSplitMethod) Number() protoreflect.EnumNumber

func (Model_DataSplitMethod) String Uses

func (x Model_DataSplitMethod) String() string

func (Model_DataSplitMethod) Type Uses

func (Model_DataSplitMethod) Type() protoreflect.EnumType

type Model_DataSplitResult Uses

type Model_DataSplitResult struct {

    // Table reference of the training data after split.
    TrainingTable *TableReference `protobuf:"bytes,1,opt,name=training_table,json=trainingTable,proto3" json:"training_table,omitempty"`
    // Table reference of the evaluation data after split.
    EvaluationTable *TableReference `protobuf:"bytes,2,opt,name=evaluation_table,json=evaluationTable,proto3" json:"evaluation_table,omitempty"`
    // contains filtered or unexported fields
}

Data split result. This contains references to the training and evaluation data tables that were used to train the model.

func (*Model_DataSplitResult) Descriptor Uses

func (*Model_DataSplitResult) Descriptor() ([]byte, []int)

Deprecated: Use Model_DataSplitResult.ProtoReflect.Descriptor instead.

func (*Model_DataSplitResult) GetEvaluationTable Uses

func (x *Model_DataSplitResult) GetEvaluationTable() *TableReference

func (*Model_DataSplitResult) GetTrainingTable Uses

func (x *Model_DataSplitResult) GetTrainingTable() *TableReference

func (*Model_DataSplitResult) ProtoMessage Uses

func (*Model_DataSplitResult) ProtoMessage()

func (*Model_DataSplitResult) ProtoReflect Uses

func (x *Model_DataSplitResult) ProtoReflect() protoreflect.Message

func (*Model_DataSplitResult) Reset Uses

func (x *Model_DataSplitResult) Reset()

func (*Model_DataSplitResult) String Uses

func (x *Model_DataSplitResult) String() string

type Model_DistanceType Uses

type Model_DistanceType int32

Distance metric used to compute the distance between two points.

const (
    Model_DISTANCE_TYPE_UNSPECIFIED Model_DistanceType = 0
    // Eculidean distance.
    Model_EUCLIDEAN Model_DistanceType = 1
    // Cosine distance.
    Model_COSINE Model_DistanceType = 2
)

func (Model_DistanceType) Descriptor Uses

func (Model_DistanceType) Descriptor() protoreflect.EnumDescriptor

func (Model_DistanceType) Enum Uses

func (x Model_DistanceType) Enum() *Model_DistanceType

func (Model_DistanceType) EnumDescriptor Uses

func (Model_DistanceType) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_DistanceType.Descriptor instead.

func (Model_DistanceType) Number Uses

func (x Model_DistanceType) Number() protoreflect.EnumNumber

func (Model_DistanceType) String Uses

func (x Model_DistanceType) String() string

func (Model_DistanceType) Type Uses

func (Model_DistanceType) Type() protoreflect.EnumType

type Model_EvaluationMetrics Uses

type Model_EvaluationMetrics struct {

    // Types that are assignable to Metrics:
    //	*Model_EvaluationMetrics_RegressionMetrics
    //	*Model_EvaluationMetrics_BinaryClassificationMetrics
    //	*Model_EvaluationMetrics_MultiClassClassificationMetrics
    //	*Model_EvaluationMetrics_ClusteringMetrics
    //	*Model_EvaluationMetrics_RankingMetrics
    //	*Model_EvaluationMetrics_ArimaForecastingMetrics
    Metrics isModel_EvaluationMetrics_Metrics `protobuf_oneof:"metrics"`
    // contains filtered or unexported fields
}

Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.

func (*Model_EvaluationMetrics) Descriptor Uses

func (*Model_EvaluationMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_EvaluationMetrics.ProtoReflect.Descriptor instead.

func (*Model_EvaluationMetrics) GetArimaForecastingMetrics Uses

func (x *Model_EvaluationMetrics) GetArimaForecastingMetrics() *Model_ArimaForecastingMetrics

func (*Model_EvaluationMetrics) GetBinaryClassificationMetrics Uses

func (x *Model_EvaluationMetrics) GetBinaryClassificationMetrics() *Model_BinaryClassificationMetrics

func (*Model_EvaluationMetrics) GetClusteringMetrics Uses

func (x *Model_EvaluationMetrics) GetClusteringMetrics() *Model_ClusteringMetrics

func (*Model_EvaluationMetrics) GetMetrics Uses

func (m *Model_EvaluationMetrics) GetMetrics() isModel_EvaluationMetrics_Metrics

func (*Model_EvaluationMetrics) GetMultiClassClassificationMetrics Uses

func (x *Model_EvaluationMetrics) GetMultiClassClassificationMetrics() *Model_MultiClassClassificationMetrics

func (*Model_EvaluationMetrics) GetRankingMetrics Uses

func (x *Model_EvaluationMetrics) GetRankingMetrics() *Model_RankingMetrics

func (*Model_EvaluationMetrics) GetRegressionMetrics Uses

func (x *Model_EvaluationMetrics) GetRegressionMetrics() *Model_RegressionMetrics

func (*Model_EvaluationMetrics) ProtoMessage Uses

func (*Model_EvaluationMetrics) ProtoMessage()

func (*Model_EvaluationMetrics) ProtoReflect Uses

func (x *Model_EvaluationMetrics) ProtoReflect() protoreflect.Message

func (*Model_EvaluationMetrics) Reset Uses

func (x *Model_EvaluationMetrics) Reset()

func (*Model_EvaluationMetrics) String Uses

func (x *Model_EvaluationMetrics) String() string

type Model_EvaluationMetrics_ArimaForecastingMetrics Uses

type Model_EvaluationMetrics_ArimaForecastingMetrics struct {
    // Populated for ARIMA models.
    ArimaForecastingMetrics *Model_ArimaForecastingMetrics `protobuf:"bytes,6,opt,name=arima_forecasting_metrics,json=arimaForecastingMetrics,proto3,oneof"`
}

type Model_EvaluationMetrics_BinaryClassificationMetrics Uses

type Model_EvaluationMetrics_BinaryClassificationMetrics struct {
    // Populated for binary classification/classifier models.
    BinaryClassificationMetrics *Model_BinaryClassificationMetrics `protobuf:"bytes,2,opt,name=binary_classification_metrics,json=binaryClassificationMetrics,proto3,oneof"`
}

type Model_EvaluationMetrics_ClusteringMetrics Uses

type Model_EvaluationMetrics_ClusteringMetrics struct {
    // Populated for clustering models.
    ClusteringMetrics *Model_ClusteringMetrics `protobuf:"bytes,4,opt,name=clustering_metrics,json=clusteringMetrics,proto3,oneof"`
}

type Model_EvaluationMetrics_MultiClassClassificationMetrics Uses

type Model_EvaluationMetrics_MultiClassClassificationMetrics struct {
    // Populated for multi-class classification/classifier models.
    MultiClassClassificationMetrics *Model_MultiClassClassificationMetrics `protobuf:"bytes,3,opt,name=multi_class_classification_metrics,json=multiClassClassificationMetrics,proto3,oneof"`
}

type Model_EvaluationMetrics_RankingMetrics Uses

type Model_EvaluationMetrics_RankingMetrics struct {
    // Populated for implicit feedback type matrix factorization models.
    RankingMetrics *Model_RankingMetrics `protobuf:"bytes,5,opt,name=ranking_metrics,json=rankingMetrics,proto3,oneof"`
}

type Model_EvaluationMetrics_RegressionMetrics Uses

type Model_EvaluationMetrics_RegressionMetrics struct {
    // Populated for regression models and explicit feedback type matrix
    // factorization models.
    RegressionMetrics *Model_RegressionMetrics `protobuf:"bytes,1,opt,name=regression_metrics,json=regressionMetrics,proto3,oneof"`
}

type Model_FeedbackType Uses

type Model_FeedbackType int32

Indicates the training algorithm to use for matrix factorization models.

const (
    Model_FEEDBACK_TYPE_UNSPECIFIED Model_FeedbackType = 0
    // Use weighted-als for implicit feedback problems.
    Model_IMPLICIT Model_FeedbackType = 1
    // Use nonweighted-als for explicit feedback problems.
    Model_EXPLICIT Model_FeedbackType = 2
)

func (Model_FeedbackType) Descriptor Uses

func (Model_FeedbackType) Descriptor() protoreflect.EnumDescriptor

func (Model_FeedbackType) Enum Uses

func (x Model_FeedbackType) Enum() *Model_FeedbackType

func (Model_FeedbackType) EnumDescriptor Uses

func (Model_FeedbackType) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_FeedbackType.Descriptor instead.

func (Model_FeedbackType) Number Uses

func (x Model_FeedbackType) Number() protoreflect.EnumNumber

func (Model_FeedbackType) String Uses

func (x Model_FeedbackType) String() string

func (Model_FeedbackType) Type Uses

func (Model_FeedbackType) Type() protoreflect.EnumType

type Model_GlobalExplanation Uses

type Model_GlobalExplanation struct {

    // A list of the top global explanations. Sorted by absolute value of
    // attribution in descending order.
    Explanations []*Model_GlobalExplanation_Explanation `protobuf:"bytes,1,rep,name=explanations,proto3" json:"explanations,omitempty"`
    // Class label for this set of global explanations. Will be empty/null for
    // binary logistic and linear regression models. Sorted alphabetically in
    // descending order.
    ClassLabel string `protobuf:"bytes,2,opt,name=class_label,json=classLabel,proto3" json:"class_label,omitempty"`
    // contains filtered or unexported fields
}

Global explanations containing the top most important features after training.

func (*Model_GlobalExplanation) Descriptor Uses

func (*Model_GlobalExplanation) Descriptor() ([]byte, []int)

Deprecated: Use Model_GlobalExplanation.ProtoReflect.Descriptor instead.

func (*Model_GlobalExplanation) GetClassLabel Uses

func (x *Model_GlobalExplanation) GetClassLabel() string

func (*Model_GlobalExplanation) GetExplanations Uses

func (x *Model_GlobalExplanation) GetExplanations() []*Model_GlobalExplanation_Explanation

func (*Model_GlobalExplanation) ProtoMessage Uses

func (*Model_GlobalExplanation) ProtoMessage()

func (*Model_GlobalExplanation) ProtoReflect Uses

func (x *Model_GlobalExplanation) ProtoReflect() protoreflect.Message

func (*Model_GlobalExplanation) Reset Uses

func (x *Model_GlobalExplanation) Reset()

func (*Model_GlobalExplanation) String Uses

func (x *Model_GlobalExplanation) String() string

type Model_GlobalExplanation_Explanation Uses

type Model_GlobalExplanation_Explanation struct {

    // Full name of the feature. For non-numerical features, will be
    // formatted like <column_name>.<encoded_feature_name>. Overall size of
    // feature name will always be truncated to first 120 characters.
    FeatureName string `protobuf:"bytes,1,opt,name=feature_name,json=featureName,proto3" json:"feature_name,omitempty"`
    // Attribution of feature.
    Attribution *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=attribution,proto3" json:"attribution,omitempty"`
    // contains filtered or unexported fields
}

Explanation for a single feature.

func (*Model_GlobalExplanation_Explanation) Descriptor Uses

func (*Model_GlobalExplanation_Explanation) Descriptor() ([]byte, []int)

Deprecated: Use Model_GlobalExplanation_Explanation.ProtoReflect.Descriptor instead.

func (*Model_GlobalExplanation_Explanation) GetAttribution Uses

func (x *Model_GlobalExplanation_Explanation) GetAttribution() *wrapperspb.DoubleValue

func (*Model_GlobalExplanation_Explanation) GetFeatureName Uses

func (x *Model_GlobalExplanation_Explanation) GetFeatureName() string

func (*Model_GlobalExplanation_Explanation) ProtoMessage Uses

func (*Model_GlobalExplanation_Explanation) ProtoMessage()

func (*Model_GlobalExplanation_Explanation) ProtoReflect Uses

func (x *Model_GlobalExplanation_Explanation) ProtoReflect() protoreflect.Message

func (*Model_GlobalExplanation_Explanation) Reset Uses

func (x *Model_GlobalExplanation_Explanation) Reset()

func (*Model_GlobalExplanation_Explanation) String Uses

func (x *Model_GlobalExplanation_Explanation) String() string

type Model_HolidayRegion Uses

type Model_HolidayRegion int32

Type of supported holiday regions for time series forecasting models.

const (
    // Holiday region unspecified.
    Model_HOLIDAY_REGION_UNSPECIFIED Model_HolidayRegion = 0
    // Global.
    Model_GLOBAL Model_HolidayRegion = 1
    // North America.
    Model_NA Model_HolidayRegion = 2
    // Japan and Asia Pacific: Korea, Greater China, India, Australia, and New
    // Zealand.
    Model_JAPAC Model_HolidayRegion = 3
    // Europe, the Middle East and Africa.
    Model_EMEA Model_HolidayRegion = 4
    // Latin America and the Caribbean.
    Model_LAC Model_HolidayRegion = 5
    // United Arab Emirates
    Model_AE Model_HolidayRegion = 6
    // Argentina
    Model_AR Model_HolidayRegion = 7
    // Austria
    Model_AT Model_HolidayRegion = 8
    // Australia
    Model_AU Model_HolidayRegion = 9
    // Belgium
    Model_BE Model_HolidayRegion = 10
    // Brazil
    Model_BR Model_HolidayRegion = 11
    // Canada
    Model_CA Model_HolidayRegion = 12
    // Switzerland
    Model_CH Model_HolidayRegion = 13
    // Chile
    Model_CL Model_HolidayRegion = 14
    // China
    Model_CN Model_HolidayRegion = 15
    // Colombia
    Model_CO Model_HolidayRegion = 16
    // Czechoslovakia
    Model_CS Model_HolidayRegion = 17
    // Czech Republic
    Model_CZ Model_HolidayRegion = 18
    // Germany
    Model_DE Model_HolidayRegion = 19
    // Denmark
    Model_DK Model_HolidayRegion = 20
    // Algeria
    Model_DZ Model_HolidayRegion = 21
    // Ecuador
    Model_EC Model_HolidayRegion = 22
    // Estonia
    Model_EE Model_HolidayRegion = 23
    // Egypt
    Model_EG Model_HolidayRegion = 24
    // Spain
    Model_ES Model_HolidayRegion = 25
    // Finland
    Model_FI Model_HolidayRegion = 26
    // France
    Model_FR Model_HolidayRegion = 27
    // Great Britain (United Kingdom)
    Model_GB Model_HolidayRegion = 28
    // Greece
    Model_GR Model_HolidayRegion = 29
    // Hong Kong
    Model_HK Model_HolidayRegion = 30
    // Hungary
    Model_HU Model_HolidayRegion = 31
    // Indonesia
    Model_ID Model_HolidayRegion = 32
    // Ireland
    Model_IE Model_HolidayRegion = 33
    // Israel
    Model_IL Model_HolidayRegion = 34
    // India
    Model_IN Model_HolidayRegion = 35
    // Iran
    Model_IR Model_HolidayRegion = 36
    // Italy
    Model_IT Model_HolidayRegion = 37
    // Japan
    Model_JP Model_HolidayRegion = 38
    // Korea (South)
    Model_KR Model_HolidayRegion = 39
    // Latvia
    Model_LV Model_HolidayRegion = 40
    // Morocco
    Model_MA Model_HolidayRegion = 41
    // Mexico
    Model_MX Model_HolidayRegion = 42
    // Malaysia
    Model_MY Model_HolidayRegion = 43
    // Nigeria
    Model_NG Model_HolidayRegion = 44
    // Netherlands
    Model_NL Model_HolidayRegion = 45
    // Norway
    Model_NO Model_HolidayRegion = 46
    // New Zealand
    Model_NZ Model_HolidayRegion = 47
    // Peru
    Model_PE Model_HolidayRegion = 48
    // Philippines
    Model_PH Model_HolidayRegion = 49
    // Pakistan
    Model_PK Model_HolidayRegion = 50
    // Poland
    Model_PL Model_HolidayRegion = 51
    // Portugal
    Model_PT Model_HolidayRegion = 52
    // Romania
    Model_RO Model_HolidayRegion = 53
    // Serbia
    Model_RS Model_HolidayRegion = 54
    // Russian Federation
    Model_RU Model_HolidayRegion = 55
    // Saudi Arabia
    Model_SA Model_HolidayRegion = 56
    // Sweden
    Model_SE Model_HolidayRegion = 57
    // Singapore
    Model_SG Model_HolidayRegion = 58
    // Slovenia
    Model_SI Model_HolidayRegion = 59
    // Slovakia
    Model_SK Model_HolidayRegion = 60
    // Thailand
    Model_TH Model_HolidayRegion = 61
    // Turkey
    Model_TR Model_HolidayRegion = 62
    // Taiwan
    Model_TW Model_HolidayRegion = 63
    // Ukraine
    Model_UA Model_HolidayRegion = 64
    // United States
    Model_US Model_HolidayRegion = 65
    // Venezuela
    Model_VE Model_HolidayRegion = 66
    // Viet Nam
    Model_VN Model_HolidayRegion = 67
    // South Africa
    Model_ZA Model_HolidayRegion = 68
)

func (Model_HolidayRegion) Descriptor Uses

func (Model_HolidayRegion) Descriptor() protoreflect.EnumDescriptor

func (Model_HolidayRegion) Enum Uses

func (x Model_HolidayRegion) Enum() *Model_HolidayRegion

func (Model_HolidayRegion) EnumDescriptor Uses

func (Model_HolidayRegion) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_HolidayRegion.Descriptor instead.

func (Model_HolidayRegion) Number Uses

func (x Model_HolidayRegion) Number() protoreflect.EnumNumber

func (Model_HolidayRegion) String Uses

func (x Model_HolidayRegion) String() string

func (Model_HolidayRegion) Type Uses

func (Model_HolidayRegion) Type() protoreflect.EnumType

type Model_KmeansEnums Uses

type Model_KmeansEnums struct {
    // contains filtered or unexported fields
}

func (*Model_KmeansEnums) Descriptor Uses

func (*Model_KmeansEnums) Descriptor() ([]byte, []int)

Deprecated: Use Model_KmeansEnums.ProtoReflect.Descriptor instead.

func (*Model_KmeansEnums) ProtoMessage Uses

func (*Model_KmeansEnums) ProtoMessage()

func (*Model_KmeansEnums) ProtoReflect Uses

func (x *Model_KmeansEnums) ProtoReflect() protoreflect.Message

func (*Model_KmeansEnums) Reset Uses

func (x *Model_KmeansEnums) Reset()

func (*Model_KmeansEnums) String Uses

func (x *Model_KmeansEnums) String() string

type Model_KmeansEnums_KmeansInitializationMethod Uses

type Model_KmeansEnums_KmeansInitializationMethod int32

Indicates the method used to initialize the centroids for KMeans clustering algorithm.

const (
    Model_KmeansEnums_KMEANS_INITIALIZATION_METHOD_UNSPECIFIED Model_KmeansEnums_KmeansInitializationMethod = 0
    // Initializes the centroids randomly.
    Model_KmeansEnums_RANDOM Model_KmeansEnums_KmeansInitializationMethod = 1
    // Initializes the centroids using data specified in
    // kmeans_initialization_column.
    Model_KmeansEnums_CUSTOM Model_KmeansEnums_KmeansInitializationMethod = 2
    // Initializes with kmeans++.
    Model_KmeansEnums_KMEANS_PLUS_PLUS Model_KmeansEnums_KmeansInitializationMethod = 3
)

func (Model_KmeansEnums_KmeansInitializationMethod) Descriptor Uses

func (Model_KmeansEnums_KmeansInitializationMethod) Descriptor() protoreflect.EnumDescriptor

func (Model_KmeansEnums_KmeansInitializationMethod) Enum Uses

func (x Model_KmeansEnums_KmeansInitializationMethod) Enum() *Model_KmeansEnums_KmeansInitializationMethod

func (Model_KmeansEnums_KmeansInitializationMethod) EnumDescriptor Uses

func (Model_KmeansEnums_KmeansInitializationMethod) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_KmeansEnums_KmeansInitializationMethod.Descriptor instead.

func (Model_KmeansEnums_KmeansInitializationMethod) Number Uses

func (x Model_KmeansEnums_KmeansInitializationMethod) Number() protoreflect.EnumNumber

func (Model_KmeansEnums_KmeansInitializationMethod) String Uses

func (x Model_KmeansEnums_KmeansInitializationMethod) String() string

func (Model_KmeansEnums_KmeansInitializationMethod) Type Uses

func (Model_KmeansEnums_KmeansInitializationMethod) Type() protoreflect.EnumType

type Model_LearnRateStrategy Uses

type Model_LearnRateStrategy int32

Indicates the learning rate optimization strategy to use.

const (
    Model_LEARN_RATE_STRATEGY_UNSPECIFIED Model_LearnRateStrategy = 0
    // Use line search to determine learning rate.
    Model_LINE_SEARCH Model_LearnRateStrategy = 1
    // Use a constant learning rate.
    Model_CONSTANT Model_LearnRateStrategy = 2
)

func (Model_LearnRateStrategy) Descriptor Uses

func (Model_LearnRateStrategy) Descriptor() protoreflect.EnumDescriptor

func (Model_LearnRateStrategy) Enum Uses

func (x Model_LearnRateStrategy) Enum() *Model_LearnRateStrategy

func (Model_LearnRateStrategy) EnumDescriptor Uses

func (Model_LearnRateStrategy) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_LearnRateStrategy.Descriptor instead.

func (Model_LearnRateStrategy) Number Uses

func (x Model_LearnRateStrategy) Number() protoreflect.EnumNumber

func (Model_LearnRateStrategy) String Uses

func (x Model_LearnRateStrategy) String() string

func (Model_LearnRateStrategy) Type Uses

func (Model_LearnRateStrategy) Type() protoreflect.EnumType

type Model_LossType Uses

type Model_LossType int32

Loss metric to evaluate model training performance.

const (
    Model_LOSS_TYPE_UNSPECIFIED Model_LossType = 0
    // Mean squared loss, used for linear regression.
    Model_MEAN_SQUARED_LOSS Model_LossType = 1
    // Mean log loss, used for logistic regression.
    Model_MEAN_LOG_LOSS Model_LossType = 2
)

func (Model_LossType) Descriptor Uses

func (Model_LossType) Descriptor() protoreflect.EnumDescriptor

func (Model_LossType) Enum Uses

func (x Model_LossType) Enum() *Model_LossType

func (Model_LossType) EnumDescriptor Uses

func (Model_LossType) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_LossType.Descriptor instead.

func (Model_LossType) Number Uses

func (x Model_LossType) Number() protoreflect.EnumNumber

func (Model_LossType) String Uses

func (x Model_LossType) String() string

func (Model_LossType) Type Uses

func (Model_LossType) Type() protoreflect.EnumType

type Model_ModelType Uses

type Model_ModelType int32

Indicates the type of the Model.

const (
    Model_MODEL_TYPE_UNSPECIFIED Model_ModelType = 0
    // Linear regression model.
    Model_LINEAR_REGRESSION Model_ModelType = 1
    // Logistic regression based classification model.
    Model_LOGISTIC_REGRESSION Model_ModelType = 2
    // K-means clustering model.
    Model_KMEANS Model_ModelType = 3
    // Matrix factorization model.
    Model_MATRIX_FACTORIZATION Model_ModelType = 4
    // [Beta] DNN classifier model.
    Model_DNN_CLASSIFIER Model_ModelType = 5
    // [Beta] An imported TensorFlow model.
    Model_TENSORFLOW Model_ModelType = 6
    // [Beta] DNN regressor model.
    Model_DNN_REGRESSOR Model_ModelType = 7
    // [Beta] Boosted tree regressor model.
    Model_BOOSTED_TREE_REGRESSOR Model_ModelType = 9
    // [Beta] Boosted tree classifier model.
    Model_BOOSTED_TREE_CLASSIFIER Model_ModelType = 10
    // [Beta] ARIMA model.
    Model_ARIMA Model_ModelType = 11
    // [Beta] AutoML Tables regression model.
    Model_AUTOML_REGRESSOR Model_ModelType = 12
    // [Beta] AutoML Tables classification model.
    Model_AUTOML_CLASSIFIER Model_ModelType = 13
)

func (Model_ModelType) Descriptor Uses

func (Model_ModelType) Descriptor() protoreflect.EnumDescriptor

func (Model_ModelType) Enum Uses

func (x Model_ModelType) Enum() *Model_ModelType

func (Model_ModelType) EnumDescriptor Uses

func (Model_ModelType) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_ModelType.Descriptor instead.

func (Model_ModelType) Number Uses

func (x Model_ModelType) Number() protoreflect.EnumNumber

func (Model_ModelType) String Uses

func (x Model_ModelType) String() string

func (Model_ModelType) Type Uses

func (Model_ModelType) Type() protoreflect.EnumType

type Model_MultiClassClassificationMetrics Uses

type Model_MultiClassClassificationMetrics struct {

    // Aggregate classification metrics.
    AggregateClassificationMetrics *Model_AggregateClassificationMetrics `protobuf:"bytes,1,opt,name=aggregate_classification_metrics,json=aggregateClassificationMetrics,proto3" json:"aggregate_classification_metrics,omitempty"`
    // Confusion matrix at different thresholds.
    ConfusionMatrixList []*Model_MultiClassClassificationMetrics_ConfusionMatrix `protobuf:"bytes,2,rep,name=confusion_matrix_list,json=confusionMatrixList,proto3" json:"confusion_matrix_list,omitempty"`
    // contains filtered or unexported fields
}

Evaluation metrics for multi-class classification/classifier models.

func (*Model_MultiClassClassificationMetrics) Descriptor Uses

func (*Model_MultiClassClassificationMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_MultiClassClassificationMetrics.ProtoReflect.Descriptor instead.

func (*Model_MultiClassClassificationMetrics) GetAggregateClassificationMetrics Uses

func (x *Model_MultiClassClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics

func (*Model_MultiClassClassificationMetrics) GetConfusionMatrixList Uses

func (x *Model_MultiClassClassificationMetrics) GetConfusionMatrixList() []*Model_MultiClassClassificationMetrics_ConfusionMatrix

func (*Model_MultiClassClassificationMetrics) ProtoMessage Uses

func (*Model_MultiClassClassificationMetrics) ProtoMessage()

func (*Model_MultiClassClassificationMetrics) ProtoReflect Uses

func (x *Model_MultiClassClassificationMetrics) ProtoReflect() protoreflect.Message

func (*Model_MultiClassClassificationMetrics) Reset Uses

func (x *Model_MultiClassClassificationMetrics) Reset()

func (*Model_MultiClassClassificationMetrics) String Uses

func (x *Model_MultiClassClassificationMetrics) String() string

type Model_MultiClassClassificationMetrics_ConfusionMatrix Uses

type Model_MultiClassClassificationMetrics_ConfusionMatrix struct {

    // Confidence threshold used when computing the entries of the
    // confusion matrix.
    ConfidenceThreshold *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=confidence_threshold,json=confidenceThreshold,proto3" json:"confidence_threshold,omitempty"`
    // One row per actual label.
    Rows []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row `protobuf:"bytes,2,rep,name=rows,proto3" json:"rows,omitempty"`
    // contains filtered or unexported fields
}

Confusion matrix for multi-class classification models.

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Descriptor Uses

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Descriptor() ([]byte, []int)

Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix.ProtoReflect.Descriptor instead.

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) GetConfidenceThreshold Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetConfidenceThreshold() *wrapperspb.DoubleValue

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) GetRows Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetRows() []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoMessage Uses

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoMessage()

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoReflect Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoReflect() protoreflect.Message

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Reset Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) Reset()

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) String Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) String() string

type Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry Uses

type Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry struct {

    // The predicted label. For confidence_threshold > 0, we will
    // also add an entry indicating the number of items under the
    // confidence threshold.
    PredictedLabel string `protobuf:"bytes,1,opt,name=predicted_label,json=predictedLabel,proto3" json:"predicted_label,omitempty"`
    // Number of items being predicted as this label.
    ItemCount *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=item_count,json=itemCount,proto3" json:"item_count,omitempty"`
    // contains filtered or unexported fields
}

A single entry in the confusion matrix.

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Descriptor Uses

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Descriptor() ([]byte, []int)

Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry.ProtoReflect.Descriptor instead.

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetItemCount Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetItemCount() *wrapperspb.Int64Value

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetPredictedLabel Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetPredictedLabel() string

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoMessage Uses

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoMessage()

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoReflect Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoReflect() protoreflect.Message

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Reset Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Reset()

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) String Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) String() string

type Model_MultiClassClassificationMetrics_ConfusionMatrix_Row Uses

type Model_MultiClassClassificationMetrics_ConfusionMatrix_Row struct {

    // The original label of this row.
    ActualLabel string `protobuf:"bytes,1,opt,name=actual_label,json=actualLabel,proto3" json:"actual_label,omitempty"`
    // Info describing predicted label distribution.
    Entries []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry `protobuf:"bytes,2,rep,name=entries,proto3" json:"entries,omitempty"`
    // contains filtered or unexported fields
}

A single row in the confusion matrix.

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Descriptor Uses

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Descriptor() ([]byte, []int)

Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix_Row.ProtoReflect.Descriptor instead.

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetActualLabel Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetActualLabel() string

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetEntries Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetEntries() []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoMessage Uses

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoMessage()

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoReflect Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoReflect() protoreflect.Message

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Reset Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Reset()

func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) String Uses

func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) String() string

type Model_OptimizationStrategy Uses

type Model_OptimizationStrategy int32

Indicates the optimization strategy used for training.

const (
    Model_OPTIMIZATION_STRATEGY_UNSPECIFIED Model_OptimizationStrategy = 0
    // Uses an iterative batch gradient descent algorithm.
    Model_BATCH_GRADIENT_DESCENT Model_OptimizationStrategy = 1
    // Uses a normal equation to solve linear regression problem.
    Model_NORMAL_EQUATION Model_OptimizationStrategy = 2
)

func (Model_OptimizationStrategy) Descriptor Uses

func (Model_OptimizationStrategy) Descriptor() protoreflect.EnumDescriptor

func (Model_OptimizationStrategy) Enum Uses

func (x Model_OptimizationStrategy) Enum() *Model_OptimizationStrategy

func (Model_OptimizationStrategy) EnumDescriptor Uses

func (Model_OptimizationStrategy) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_OptimizationStrategy.Descriptor instead.

func (Model_OptimizationStrategy) Number Uses

func (x Model_OptimizationStrategy) Number() protoreflect.EnumNumber

func (Model_OptimizationStrategy) String Uses

func (x Model_OptimizationStrategy) String() string

func (Model_OptimizationStrategy) Type Uses

func (Model_OptimizationStrategy) Type() protoreflect.EnumType

type Model_RankingMetrics Uses

type Model_RankingMetrics struct {

    // Calculates a precision per user for all the items by ranking them and
    // then averages all the precisions across all the users.
    MeanAveragePrecision *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=mean_average_precision,json=meanAveragePrecision,proto3" json:"mean_average_precision,omitempty"`
    // Similar to the mean squared error computed in regression and explicit
    // recommendation models except instead of computing the rating directly,
    // the output from evaluate is computed against a preference which is 1 or 0
    // depending on if the rating exists or not.
    MeanSquaredError *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_error,json=meanSquaredError,proto3" json:"mean_squared_error,omitempty"`
    // A metric to determine the goodness of a ranking calculated from the
    // predicted confidence by comparing it to an ideal rank measured by the
    // original ratings.
    NormalizedDiscountedCumulativeGain *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=normalized_discounted_cumulative_gain,json=normalizedDiscountedCumulativeGain,proto3" json:"normalized_discounted_cumulative_gain,omitempty"`
    // Determines the goodness of a ranking by computing the percentile rank
    // from the predicted confidence and dividing it by the original rank.
    AverageRank *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=average_rank,json=averageRank,proto3" json:"average_rank,omitempty"`
    // contains filtered or unexported fields
}

Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.

func (*Model_RankingMetrics) Descriptor Uses

func (*Model_RankingMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_RankingMetrics.ProtoReflect.Descriptor instead.

func (*Model_RankingMetrics) GetAverageRank Uses

func (x *Model_RankingMetrics) GetAverageRank() *wrapperspb.DoubleValue

func (*Model_RankingMetrics) GetMeanAveragePrecision Uses

func (x *Model_RankingMetrics) GetMeanAveragePrecision() *wrapperspb.DoubleValue

func (*Model_RankingMetrics) GetMeanSquaredError Uses

func (x *Model_RankingMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue

func (*Model_RankingMetrics) GetNormalizedDiscountedCumulativeGain Uses

func (x *Model_RankingMetrics) GetNormalizedDiscountedCumulativeGain() *wrapperspb.DoubleValue

func (*Model_RankingMetrics) ProtoMessage Uses

func (*Model_RankingMetrics) ProtoMessage()

func (*Model_RankingMetrics) ProtoReflect Uses

func (x *Model_RankingMetrics) ProtoReflect() protoreflect.Message

func (*Model_RankingMetrics) Reset Uses

func (x *Model_RankingMetrics) Reset()

func (*Model_RankingMetrics) String Uses

func (x *Model_RankingMetrics) String() string

type Model_RegressionMetrics Uses

type Model_RegressionMetrics struct {

    // Mean absolute error.
    MeanAbsoluteError *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=mean_absolute_error,json=meanAbsoluteError,proto3" json:"mean_absolute_error,omitempty"`
    // Mean squared error.
    MeanSquaredError *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_error,json=meanSquaredError,proto3" json:"mean_squared_error,omitempty"`
    // Mean squared log error.
    MeanSquaredLogError *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=mean_squared_log_error,json=meanSquaredLogError,proto3" json:"mean_squared_log_error,omitempty"`
    // Median absolute error.
    MedianAbsoluteError *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=median_absolute_error,json=medianAbsoluteError,proto3" json:"median_absolute_error,omitempty"`
    // R^2 score.
    RSquared *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=r_squared,json=rSquared,proto3" json:"r_squared,omitempty"`
    // contains filtered or unexported fields
}

Evaluation metrics for regression and explicit feedback type matrix factorization models.

func (*Model_RegressionMetrics) Descriptor Uses

func (*Model_RegressionMetrics) Descriptor() ([]byte, []int)

Deprecated: Use Model_RegressionMetrics.ProtoReflect.Descriptor instead.

func (*Model_RegressionMetrics) GetMeanAbsoluteError Uses

func (x *Model_RegressionMetrics) GetMeanAbsoluteError() *wrapperspb.DoubleValue

func (*Model_RegressionMetrics) GetMeanSquaredError Uses

func (x *Model_RegressionMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue

func (*Model_RegressionMetrics) GetMeanSquaredLogError Uses

func (x *Model_RegressionMetrics) GetMeanSquaredLogError() *wrapperspb.DoubleValue

func (*Model_RegressionMetrics) GetMedianAbsoluteError Uses

func (x *Model_RegressionMetrics) GetMedianAbsoluteError() *wrapperspb.DoubleValue

func (*Model_RegressionMetrics) GetRSquared Uses

func (x *Model_RegressionMetrics) GetRSquared() *wrapperspb.DoubleValue

func (*Model_RegressionMetrics) ProtoMessage Uses

func (*Model_RegressionMetrics) ProtoMessage()

func (*Model_RegressionMetrics) ProtoReflect Uses

func (x *Model_RegressionMetrics) ProtoReflect() protoreflect.Message

func (*Model_RegressionMetrics) Reset Uses

func (x *Model_RegressionMetrics) Reset()

func (*Model_RegressionMetrics) String Uses

func (x *Model_RegressionMetrics) String() string

type Model_SeasonalPeriod Uses

type Model_SeasonalPeriod struct {
    // contains filtered or unexported fields
}

func (*Model_SeasonalPeriod) Descriptor Uses

func (*Model_SeasonalPeriod) Descriptor() ([]byte, []int)

Deprecated: Use Model_SeasonalPeriod.ProtoReflect.Descriptor instead.

func (*Model_SeasonalPeriod) ProtoMessage Uses

func (*Model_SeasonalPeriod) ProtoMessage()

func (*Model_SeasonalPeriod) ProtoReflect Uses

func (x *Model_SeasonalPeriod) ProtoReflect() protoreflect.Message

func (*Model_SeasonalPeriod) Reset Uses

func (x *Model_SeasonalPeriod) Reset()

func (*Model_SeasonalPeriod) String Uses

func (x *Model_SeasonalPeriod) String() string

type Model_SeasonalPeriod_SeasonalPeriodType Uses

type Model_SeasonalPeriod_SeasonalPeriodType int32
const (
    Model_SeasonalPeriod_SEASONAL_PERIOD_TYPE_UNSPECIFIED Model_SeasonalPeriod_SeasonalPeriodType = 0
    // No seasonality
    Model_SeasonalPeriod_NO_SEASONALITY Model_SeasonalPeriod_SeasonalPeriodType = 1
    // Daily period, 24 hours.
    Model_SeasonalPeriod_DAILY Model_SeasonalPeriod_SeasonalPeriodType = 2
    // Weekly period, 7 days.
    Model_SeasonalPeriod_WEEKLY Model_SeasonalPeriod_SeasonalPeriodType = 3
    // Monthly period, 30 days or irregular.
    Model_SeasonalPeriod_MONTHLY Model_SeasonalPeriod_SeasonalPeriodType = 4
    // Quarterly period, 90 days or irregular.
    Model_SeasonalPeriod_QUARTERLY Model_SeasonalPeriod_SeasonalPeriodType = 5
    // Yearly period, 365 days or irregular.
    Model_SeasonalPeriod_YEARLY Model_SeasonalPeriod_SeasonalPeriodType = 6
)

func (Model_SeasonalPeriod_SeasonalPeriodType) Descriptor Uses

func (Model_SeasonalPeriod_SeasonalPeriodType) Descriptor() protoreflect.EnumDescriptor

func (Model_SeasonalPeriod_SeasonalPeriodType) Enum Uses

func (x Model_SeasonalPeriod_SeasonalPeriodType) Enum() *Model_SeasonalPeriod_SeasonalPeriodType

func (Model_SeasonalPeriod_SeasonalPeriodType) EnumDescriptor Uses

func (Model_SeasonalPeriod_SeasonalPeriodType) EnumDescriptor() ([]byte, []int)

Deprecated: Use Model_SeasonalPeriod_SeasonalPeriodType.Descriptor instead.

func (Model_SeasonalPeriod_SeasonalPeriodType) Number Uses

func (x Model_SeasonalPeriod_SeasonalPeriodType) Number() protoreflect.EnumNumber

func (Model_SeasonalPeriod_SeasonalPeriodType) String Uses

func (x Model_SeasonalPeriod_SeasonalPeriodType) String() string

func (Model_SeasonalPeriod_SeasonalPeriodType) Type Uses

func (Model_SeasonalPeriod_SeasonalPeriodType) Type() protoreflect.EnumType

type Model_TrainingRun Uses

type Model_TrainingRun struct {

    // Options that were used for this training run, includes
    // user specified and default options that were used.
    TrainingOptions *Model_TrainingRun_TrainingOptions `protobuf:"bytes,1,opt,name=training_options,json=trainingOptions,proto3" json:"training_options,omitempty"`
    // The start time of this training run.
    StartTime *timestamppb.Timestamp `protobuf:"bytes,8,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
    // Output of each iteration run, results.size() <= max_iterations.
    Results []*Model_TrainingRun_IterationResult `protobuf:"bytes,6,rep,name=results,proto3" json:"results,omitempty"`
    // The evaluation metrics over training/eval data that were computed at the
    // end of training.
    EvaluationMetrics *Model_EvaluationMetrics `protobuf:"bytes,7,opt,name=evaluation_metrics,json=evaluationMetrics,proto3" json:"evaluation_metrics,omitempty"`
    // Data split result of the training run. Only set when the input data is
    // actually split.
    DataSplitResult *Model_DataSplitResult `protobuf:"bytes,9,opt,name=data_split_result,json=dataSplitResult,proto3" json:"data_split_result,omitempty"`
    // Global explanations for important features of the model. For multi-class
    // models, there is one entry for each label class. For other models, there
    // is only one entry in the list.
    GlobalExplanations []*Model_GlobalExplanation `protobuf:"bytes,10,rep,name=global_explanations,json=globalExplanations,proto3" json:"global_explanations,omitempty"`
    // contains filtered or unexported fields
}

Information about a single training query run for the model.

func (*Model_TrainingRun) Descriptor Uses

func (*Model_TrainingRun) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun) GetDataSplitResult Uses

func (x *Model_TrainingRun) GetDataSplitResult() *Model_DataSplitResult

func (*Model_TrainingRun) GetEvaluationMetrics Uses

func (x *Model_TrainingRun) GetEvaluationMetrics() *Model_EvaluationMetrics

func (*Model_TrainingRun) GetGlobalExplanations Uses

func (x *Model_TrainingRun) GetGlobalExplanations() []*Model_GlobalExplanation

func (*Model_TrainingRun) GetResults Uses

func (x *Model_TrainingRun) GetResults() []*Model_TrainingRun_IterationResult

func (*Model_TrainingRun) GetStartTime Uses

func (x *Model_TrainingRun) GetStartTime() *timestamppb.Timestamp

func (*Model_TrainingRun) GetTrainingOptions Uses

func (x *Model_TrainingRun) GetTrainingOptions() *Model_TrainingRun_TrainingOptions

func (*Model_TrainingRun) ProtoMessage Uses

func (*Model_TrainingRun) ProtoMessage()

func (*Model_TrainingRun) ProtoReflect Uses

func (x *Model_TrainingRun) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun) Reset Uses

func (x *Model_TrainingRun) Reset()

func (*Model_TrainingRun) String Uses

func (x *Model_TrainingRun) String() string

type Model_TrainingRun_IterationResult Uses

type Model_TrainingRun_IterationResult struct {

    // Index of the iteration, 0 based.
    Index *wrapperspb.Int32Value `protobuf:"bytes,1,opt,name=index,proto3" json:"index,omitempty"`
    // Time taken to run the iteration in milliseconds.
    DurationMs *wrapperspb.Int64Value `protobuf:"bytes,4,opt,name=duration_ms,json=durationMs,proto3" json:"duration_ms,omitempty"`
    // Loss computed on the training data at the end of iteration.
    TrainingLoss *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=training_loss,json=trainingLoss,proto3" json:"training_loss,omitempty"`
    // Loss computed on the eval data at the end of iteration.
    EvalLoss *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=eval_loss,json=evalLoss,proto3" json:"eval_loss,omitempty"`
    // Learn rate used for this iteration.
    LearnRate float64 `protobuf:"fixed64,7,opt,name=learn_rate,json=learnRate,proto3" json:"learn_rate,omitempty"`
    // Information about top clusters for clustering models.
    ClusterInfos []*Model_TrainingRun_IterationResult_ClusterInfo `protobuf:"bytes,8,rep,name=cluster_infos,json=clusterInfos,proto3" json:"cluster_infos,omitempty"`
    ArimaResult  *Model_TrainingRun_IterationResult_ArimaResult   `protobuf:"bytes,9,opt,name=arima_result,json=arimaResult,proto3" json:"arima_result,omitempty"`
    // contains filtered or unexported fields
}

Information about a single iteration of the training run.

func (*Model_TrainingRun_IterationResult) Descriptor Uses

func (*Model_TrainingRun_IterationResult) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun_IterationResult.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun_IterationResult) GetArimaResult Uses

func (x *Model_TrainingRun_IterationResult) GetArimaResult() *Model_TrainingRun_IterationResult_ArimaResult

func (*Model_TrainingRun_IterationResult) GetClusterInfos Uses

func (x *Model_TrainingRun_IterationResult) GetClusterInfos() []*Model_TrainingRun_IterationResult_ClusterInfo

func (*Model_TrainingRun_IterationResult) GetDurationMs Uses

func (x *Model_TrainingRun_IterationResult) GetDurationMs() *wrapperspb.Int64Value

func (*Model_TrainingRun_IterationResult) GetEvalLoss Uses

func (x *Model_TrainingRun_IterationResult) GetEvalLoss() *wrapperspb.DoubleValue

func (*Model_TrainingRun_IterationResult) GetIndex Uses

func (x *Model_TrainingRun_IterationResult) GetIndex() *wrapperspb.Int32Value

func (*Model_TrainingRun_IterationResult) GetLearnRate Uses

func (x *Model_TrainingRun_IterationResult) GetLearnRate() float64

func (*Model_TrainingRun_IterationResult) GetTrainingLoss Uses

func (x *Model_TrainingRun_IterationResult) GetTrainingLoss() *wrapperspb.DoubleValue

func (*Model_TrainingRun_IterationResult) ProtoMessage Uses

func (*Model_TrainingRun_IterationResult) ProtoMessage()

func (*Model_TrainingRun_IterationResult) ProtoReflect Uses

func (x *Model_TrainingRun_IterationResult) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun_IterationResult) Reset Uses

func (x *Model_TrainingRun_IterationResult) Reset()

func (*Model_TrainingRun_IterationResult) String Uses

func (x *Model_TrainingRun_IterationResult) String() string

type Model_TrainingRun_IterationResult_ArimaResult Uses

type Model_TrainingRun_IterationResult_ArimaResult struct {

    // This message is repeated because there are multiple arima models
    // fitted in auto-arima. For non-auto-arima model, its size is one.
    ArimaModelInfo []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo `protobuf:"bytes,1,rep,name=arima_model_info,json=arimaModelInfo,proto3" json:"arima_model_info,omitempty"`
    // Seasonal periods. Repeated because multiple periods are supported for
    // one time series.
    SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,2,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
    // contains filtered or unexported fields
}

(Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results.

func (*Model_TrainingRun_IterationResult_ArimaResult) Descriptor Uses

func (*Model_TrainingRun_IterationResult_ArimaResult) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun_IterationResult_ArimaResult) GetArimaModelInfo Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult) GetArimaModelInfo() []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo

func (*Model_TrainingRun_IterationResult_ArimaResult) GetSeasonalPeriods Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType

func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoMessage Uses

func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoMessage()

func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoReflect Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun_IterationResult_ArimaResult) Reset Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult) Reset()

func (*Model_TrainingRun_IterationResult_ArimaResult) String Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult) String() string

type Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients Uses

type Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients struct {

    // Auto-regressive coefficients, an array of double.
    AutoRegressiveCoefficients []float64 `protobuf:"fixed64,1,rep,packed,name=auto_regressive_coefficients,json=autoRegressiveCoefficients,proto3" json:"auto_regressive_coefficients,omitempty"`
    // Moving-average coefficients, an array of double.
    MovingAverageCoefficients []float64 `protobuf:"fixed64,2,rep,packed,name=moving_average_coefficients,json=movingAverageCoefficients,proto3" json:"moving_average_coefficients,omitempty"`
    // Intercept coefficient, just a double not an array.
    InterceptCoefficient float64 `protobuf:"fixed64,3,opt,name=intercept_coefficient,json=interceptCoefficient,proto3" json:"intercept_coefficient,omitempty"`
    // contains filtered or unexported fields
}

Arima coefficients.

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Descriptor Uses

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetAutoRegressiveCoefficients Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetAutoRegressiveCoefficients() []float64

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetInterceptCoefficient Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetInterceptCoefficient() float64

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetMovingAverageCoefficients Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetMovingAverageCoefficients() []float64

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoMessage Uses

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoMessage()

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoReflect Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Reset Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Reset()

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) String Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) String() string

type Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo Uses

type Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo struct {

    // Non-seasonal order.
    NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,1,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
    // Arima coefficients.
    ArimaCoefficients *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients `protobuf:"bytes,2,opt,name=arima_coefficients,json=arimaCoefficients,proto3" json:"arima_coefficients,omitempty"`
    // Arima fitting metrics.
    ArimaFittingMetrics *Model_ArimaFittingMetrics `protobuf:"bytes,3,opt,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"`
    // Whether Arima model fitted with drift or not. It is always false
    // when d is not 1.
    HasDrift bool `protobuf:"varint,4,opt,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"`
    // The id to indicate different time series.
    TimeSeriesId string `protobuf:"bytes,5,opt,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"`
    // Seasonal periods. Repeated because multiple periods are supported
    // for one time series.
    SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,6,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
    // contains filtered or unexported fields
}

Arima model information.

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Descriptor Uses

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaCoefficients Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaCoefficients() *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaFittingMetrics Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaFittingMetrics() *Model_ArimaFittingMetrics

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasDrift Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasDrift() bool

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetNonSeasonalOrder Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetNonSeasonalOrder() *Model_ArimaOrder

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetSeasonalPeriods Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesId Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesId() string

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoMessage Uses

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoMessage()

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoReflect Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Reset Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Reset()

func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) String Uses

func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) String() string

type Model_TrainingRun_IterationResult_ClusterInfo Uses

type Model_TrainingRun_IterationResult_ClusterInfo struct {

    // Centroid id.
    CentroidId int64 `protobuf:"varint,1,opt,name=centroid_id,json=centroidId,proto3" json:"centroid_id,omitempty"`
    // Cluster radius, the average distance from centroid
    // to each point assigned to the cluster.
    ClusterRadius *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=cluster_radius,json=clusterRadius,proto3" json:"cluster_radius,omitempty"`
    // Cluster size, the total number of points assigned to the cluster.
    ClusterSize *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=cluster_size,json=clusterSize,proto3" json:"cluster_size,omitempty"`
    // contains filtered or unexported fields
}

Information about a single cluster for clustering model.

func (*Model_TrainingRun_IterationResult_ClusterInfo) Descriptor Uses

func (*Model_TrainingRun_IterationResult_ClusterInfo) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun_IterationResult_ClusterInfo.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun_IterationResult_ClusterInfo) GetCentroidId Uses

func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetCentroidId() int64

func (*Model_TrainingRun_IterationResult_ClusterInfo) GetClusterRadius Uses

func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterRadius() *wrapperspb.DoubleValue

func (*Model_TrainingRun_IterationResult_ClusterInfo) GetClusterSize Uses

func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterSize() *wrapperspb.Int64Value

func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoMessage Uses

func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoMessage()

func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoReflect Uses

func (x *Model_TrainingRun_IterationResult_ClusterInfo) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun_IterationResult_ClusterInfo) Reset Uses

func (x *Model_TrainingRun_IterationResult_ClusterInfo) Reset()

func (*Model_TrainingRun_IterationResult_ClusterInfo) String Uses

func (x *Model_TrainingRun_IterationResult_ClusterInfo) String() string

type Model_TrainingRun_TrainingOptions Uses

type Model_TrainingRun_TrainingOptions struct {

    // The maximum number of iterations in training. Used only for iterative
    // training algorithms.
    MaxIterations int64 `protobuf:"varint,1,opt,name=max_iterations,json=maxIterations,proto3" json:"max_iterations,omitempty"`
    // Type of loss function used during training run.
    LossType Model_LossType `protobuf:"varint,2,opt,name=loss_type,json=lossType,proto3,enum=google.cloud.bigquery.v2.Model_LossType" json:"loss_type,omitempty"`
    // Learning rate in training. Used only for iterative training algorithms.
    LearnRate float64 `protobuf:"fixed64,3,opt,name=learn_rate,json=learnRate,proto3" json:"learn_rate,omitempty"`
    // L1 regularization coefficient.
    L1Regularization *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=l1_regularization,json=l1Regularization,proto3" json:"l1_regularization,omitempty"`
    // L2 regularization coefficient.
    L2Regularization *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=l2_regularization,json=l2Regularization,proto3" json:"l2_regularization,omitempty"`
    // When early_stop is true, stops training when accuracy improvement is
    // less than 'min_relative_progress'. Used only for iterative training
    // algorithms.
    MinRelativeProgress *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=min_relative_progress,json=minRelativeProgress,proto3" json:"min_relative_progress,omitempty"`
    // Whether to train a model from the last checkpoint.
    WarmStart *wrapperspb.BoolValue `protobuf:"bytes,7,opt,name=warm_start,json=warmStart,proto3" json:"warm_start,omitempty"`
    // Whether to stop early when the loss doesn't improve significantly
    // any more (compared to min_relative_progress). Used only for iterative
    // training algorithms.
    EarlyStop *wrapperspb.BoolValue `protobuf:"bytes,8,opt,name=early_stop,json=earlyStop,proto3" json:"early_stop,omitempty"`
    // Name of input label columns in training data.
    InputLabelColumns []string `protobuf:"bytes,9,rep,name=input_label_columns,json=inputLabelColumns,proto3" json:"input_label_columns,omitempty"`
    // The data split type for training and evaluation, e.g. RANDOM.
    DataSplitMethod Model_DataSplitMethod `protobuf:"varint,10,opt,name=data_split_method,json=dataSplitMethod,proto3,enum=google.cloud.bigquery.v2.Model_DataSplitMethod" json:"data_split_method,omitempty"`
    // The fraction of evaluation data over the whole input data. The rest
    // of data will be used as training data. The format should be double.
    // Accurate to two decimal places.
    // Default value is 0.2.
    DataSplitEvalFraction float64 `protobuf:"fixed64,11,opt,name=data_split_eval_fraction,json=dataSplitEvalFraction,proto3" json:"data_split_eval_fraction,omitempty"`
    // The column to split data with. This column won't be used as a
    // feature.
    // 1. When data_split_method is CUSTOM, the corresponding column should
    // be boolean. The rows with true value tag are eval data, and the false
    // are training data.
    // 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION
    // rows (from smallest to largest) in the corresponding column are used
    // as training data, and the rest are eval data. It respects the order
    // in Orderable data types:
    // https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties
    DataSplitColumn string `protobuf:"bytes,12,opt,name=data_split_column,json=dataSplitColumn,proto3" json:"data_split_column,omitempty"`
    // The strategy to determine learn rate for the current iteration.
    LearnRateStrategy Model_LearnRateStrategy `protobuf:"varint,13,opt,name=learn_rate_strategy,json=learnRateStrategy,proto3,enum=google.cloud.bigquery.v2.Model_LearnRateStrategy" json:"learn_rate_strategy,omitempty"`
    // Specifies the initial learning rate for the line search learn rate
    // strategy.
    InitialLearnRate float64 `protobuf:"fixed64,16,opt,name=initial_learn_rate,json=initialLearnRate,proto3" json:"initial_learn_rate,omitempty"`
    // Weights associated with each label class, for rebalancing the
    // training data. Only applicable for classification models.
    LabelClassWeights map[string]float64 `protobuf:"bytes,17,rep,name=label_class_weights,json=labelClassWeights,proto3" json:"label_class_weights,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"fixed64,2,opt,name=value,proto3"`
    // User column specified for matrix factorization models.
    UserColumn string `protobuf:"bytes,18,opt,name=user_column,json=userColumn,proto3" json:"user_column,omitempty"`
    // Item column specified for matrix factorization models.
    ItemColumn string `protobuf:"bytes,19,opt,name=item_column,json=itemColumn,proto3" json:"item_column,omitempty"`
    // Distance type for clustering models.
    DistanceType Model_DistanceType `protobuf:"varint,20,opt,name=distance_type,json=distanceType,proto3,enum=google.cloud.bigquery.v2.Model_DistanceType" json:"distance_type,omitempty"`
    // Number of clusters for clustering models.
    NumClusters int64 `protobuf:"varint,21,opt,name=num_clusters,json=numClusters,proto3" json:"num_clusters,omitempty"`
    // [Beta] Google Cloud Storage URI from which the model was imported. Only
    // applicable for imported models.
    ModelUri string `protobuf:"bytes,22,opt,name=model_uri,json=modelUri,proto3" json:"model_uri,omitempty"`
    // Optimization strategy for training linear regression models.
    OptimizationStrategy Model_OptimizationStrategy `protobuf:"varint,23,opt,name=optimization_strategy,json=optimizationStrategy,proto3,enum=google.cloud.bigquery.v2.Model_OptimizationStrategy" json:"optimization_strategy,omitempty"`
    // Hidden units for dnn models.
    HiddenUnits []int64 `protobuf:"varint,24,rep,packed,name=hidden_units,json=hiddenUnits,proto3" json:"hidden_units,omitempty"`
    // Batch size for dnn models.
    BatchSize int64 `protobuf:"varint,25,opt,name=batch_size,json=batchSize,proto3" json:"batch_size,omitempty"`
    // Dropout probability for dnn models.
    Dropout *wrapperspb.DoubleValue `protobuf:"bytes,26,opt,name=dropout,proto3" json:"dropout,omitempty"`
    // Maximum depth of a tree for boosted tree models.
    MaxTreeDepth int64 `protobuf:"varint,27,opt,name=max_tree_depth,json=maxTreeDepth,proto3" json:"max_tree_depth,omitempty"`
    // Subsample fraction of the training data to grow tree to prevent
    // overfitting for boosted tree models.
    Subsample float64 `protobuf:"fixed64,28,opt,name=subsample,proto3" json:"subsample,omitempty"`
    // Minimum split loss for boosted tree models.
    MinSplitLoss *wrapperspb.DoubleValue `protobuf:"bytes,29,opt,name=min_split_loss,json=minSplitLoss,proto3" json:"min_split_loss,omitempty"`
    // Num factors specified for matrix factorization models.
    NumFactors int64 `protobuf:"varint,30,opt,name=num_factors,json=numFactors,proto3" json:"num_factors,omitempty"`
    // Feedback type that specifies which algorithm to run for matrix
    // factorization.
    FeedbackType Model_FeedbackType `protobuf:"varint,31,opt,name=feedback_type,json=feedbackType,proto3,enum=google.cloud.bigquery.v2.Model_FeedbackType" json:"feedback_type,omitempty"`
    // Hyperparameter for matrix factoration when implicit feedback type is
    // specified.
    WalsAlpha *wrapperspb.DoubleValue `protobuf:"bytes,32,opt,name=wals_alpha,json=walsAlpha,proto3" json:"wals_alpha,omitempty"`
    // The method used to initialize the centroids for kmeans algorithm.
    KmeansInitializationMethod Model_KmeansEnums_KmeansInitializationMethod `protobuf:"varint,33,opt,name=kmeans_initialization_method,json=kmeansInitializationMethod,proto3,enum=google.cloud.bigquery.v2.Model_KmeansEnums_KmeansInitializationMethod" json:"kmeans_initialization_method,omitempty"`
    // The column used to provide the initial centroids for kmeans algorithm
    // when kmeans_initialization_method is CUSTOM.
    KmeansInitializationColumn string `protobuf:"bytes,34,opt,name=kmeans_initialization_column,json=kmeansInitializationColumn,proto3" json:"kmeans_initialization_column,omitempty"`
    // Column to be designated as time series timestamp for ARIMA model.
    TimeSeriesTimestampColumn string `protobuf:"bytes,35,opt,name=time_series_timestamp_column,json=timeSeriesTimestampColumn,proto3" json:"time_series_timestamp_column,omitempty"`
    // Column to be designated as time series data for ARIMA model.
    TimeSeriesDataColumn string `protobuf:"bytes,36,opt,name=time_series_data_column,json=timeSeriesDataColumn,proto3" json:"time_series_data_column,omitempty"`
    // Whether to enable auto ARIMA or not.
    AutoArima bool `protobuf:"varint,37,opt,name=auto_arima,json=autoArima,proto3" json:"auto_arima,omitempty"`
    // A specification of the non-seasonal part of the ARIMA model: the three
    // components (p, d, q) are the AR order, the degree of differencing, and
    // the MA order.
    NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,38,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
    // The data frequency of a time series.
    DataFrequency Model_DataFrequency `protobuf:"varint,39,opt,name=data_frequency,json=dataFrequency,proto3,enum=google.cloud.bigquery.v2.Model_DataFrequency" json:"data_frequency,omitempty"`
    // Include drift when fitting an ARIMA model.
    IncludeDrift bool `protobuf:"varint,41,opt,name=include_drift,json=includeDrift,proto3" json:"include_drift,omitempty"`
    // The geographical region based on which the holidays are considered in
    // time series modeling. If a valid value is specified, then holiday
    // effects modeling is enabled.
    HolidayRegion Model_HolidayRegion `protobuf:"varint,42,opt,name=holiday_region,json=holidayRegion,proto3,enum=google.cloud.bigquery.v2.Model_HolidayRegion" json:"holiday_region,omitempty"`
    // The id column that will be used to indicate different time series to
    // forecast in parallel.
    TimeSeriesIdColumn string `protobuf:"bytes,43,opt,name=time_series_id_column,json=timeSeriesIdColumn,proto3" json:"time_series_id_column,omitempty"`
    // The number of periods ahead that need to be forecasted.
    Horizon int64 `protobuf:"varint,44,opt,name=horizon,proto3" json:"horizon,omitempty"`
    // Whether to preserve the input structs in output feature names.
    // Suppose there is a struct A with field b.
    // When false (default), the output feature name is A_b.
    // When true, the output feature name is A.b.
    PreserveInputStructs bool `protobuf:"varint,45,opt,name=preserve_input_structs,json=preserveInputStructs,proto3" json:"preserve_input_structs,omitempty"`
    // The max value of non-seasonal p and q.
    AutoArimaMaxOrder int64 `protobuf:"varint,46,opt,name=auto_arima_max_order,json=autoArimaMaxOrder,proto3" json:"auto_arima_max_order,omitempty"`
    // contains filtered or unexported fields
}

func (*Model_TrainingRun_TrainingOptions) Descriptor Uses

func (*Model_TrainingRun_TrainingOptions) Descriptor() ([]byte, []int)

Deprecated: Use Model_TrainingRun_TrainingOptions.ProtoReflect.Descriptor instead.

func (*Model_TrainingRun_TrainingOptions) GetAutoArima Uses

func (x *Model_TrainingRun_TrainingOptions) GetAutoArima() bool

func (*Model_TrainingRun_TrainingOptions) GetAutoArimaMaxOrder Uses

func (x *Model_TrainingRun_TrainingOptions) GetAutoArimaMaxOrder() int64

func (*Model_TrainingRun_TrainingOptions) GetBatchSize Uses

func (x *Model_TrainingRun_TrainingOptions) GetBatchSize() int64

func (*Model_TrainingRun_TrainingOptions) GetDataFrequency Uses

func (x *Model_TrainingRun_TrainingOptions) GetDataFrequency() Model_DataFrequency

func (*Model_TrainingRun_TrainingOptions) GetDataSplitColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetDataSplitColumn() string

func (*Model_TrainingRun_TrainingOptions) GetDataSplitEvalFraction Uses

func (x *Model_TrainingRun_TrainingOptions) GetDataSplitEvalFraction() float64

func (*Model_TrainingRun_TrainingOptions) GetDataSplitMethod Uses

func (x *Model_TrainingRun_TrainingOptions) GetDataSplitMethod() Model_DataSplitMethod

func (*Model_TrainingRun_TrainingOptions) GetDistanceType Uses

func (x *Model_TrainingRun_TrainingOptions) GetDistanceType() Model_DistanceType

func (*Model_TrainingRun_TrainingOptions) GetDropout Uses

func (x *Model_TrainingRun_TrainingOptions) GetDropout() *wrapperspb.DoubleValue

func (*Model_TrainingRun_TrainingOptions) GetEarlyStop Uses

func (x *Model_TrainingRun_TrainingOptions) GetEarlyStop() *wrapperspb.BoolValue

func (*Model_TrainingRun_TrainingOptions) GetFeedbackType Uses

func (x *Model_TrainingRun_TrainingOptions) GetFeedbackType() Model_FeedbackType

func (*Model_TrainingRun_TrainingOptions) GetHiddenUnits Uses

func (x *Model_TrainingRun_TrainingOptions) GetHiddenUnits() []int64

func (*Model_TrainingRun_TrainingOptions) GetHolidayRegion Uses

func (x *Model_TrainingRun_TrainingOptions) GetHolidayRegion() Model_HolidayRegion

func (*Model_TrainingRun_TrainingOptions) GetHorizon Uses

func (x *Model_TrainingRun_TrainingOptions) GetHorizon() int64

func (*Model_TrainingRun_TrainingOptions) GetIncludeDrift Uses

func (x *Model_TrainingRun_TrainingOptions) GetIncludeDrift() bool

func (*Model_TrainingRun_TrainingOptions) GetInitialLearnRate Uses

func (x *Model_TrainingRun_TrainingOptions) GetInitialLearnRate() float64

func (*Model_TrainingRun_TrainingOptions) GetInputLabelColumns Uses

func (x *Model_TrainingRun_TrainingOptions) GetInputLabelColumns() []string

func (*Model_TrainingRun_TrainingOptions) GetItemColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetItemColumn() string

func (*Model_TrainingRun_TrainingOptions) GetKmeansInitializationColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationColumn() string

func (*Model_TrainingRun_TrainingOptions) GetKmeansInitializationMethod Uses

func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationMethod() Model_KmeansEnums_KmeansInitializationMethod

func (*Model_TrainingRun_TrainingOptions) GetL1Regularization Uses

func (x *Model_TrainingRun_TrainingOptions) GetL1Regularization() *wrapperspb.DoubleValue

func (*Model_TrainingRun_TrainingOptions) GetL2Regularization Uses

func (x *Model_TrainingRun_TrainingOptions) GetL2Regularization() *wrapperspb.DoubleValue

func (*Model_TrainingRun_TrainingOptions) GetLabelClassWeights Uses

func (x *Model_TrainingRun_TrainingOptions) GetLabelClassWeights() map[string]float64

func (*Model_TrainingRun_TrainingOptions) GetLearnRate Uses

func (x *Model_TrainingRun_TrainingOptions) GetLearnRate() float64

func (*Model_TrainingRun_TrainingOptions) GetLearnRateStrategy Uses

func (x *Model_TrainingRun_TrainingOptions) GetLearnRateStrategy() Model_LearnRateStrategy

func (*Model_TrainingRun_TrainingOptions) GetLossType Uses

func (x *Model_TrainingRun_TrainingOptions) GetLossType() Model_LossType

func (*Model_TrainingRun_TrainingOptions) GetMaxIterations Uses

func (x *Model_TrainingRun_TrainingOptions) GetMaxIterations() int64

func (*Model_TrainingRun_TrainingOptions) GetMaxTreeDepth Uses

func (x *Model_TrainingRun_TrainingOptions) GetMaxTreeDepth() int64

func (*Model_TrainingRun_TrainingOptions) GetMinRelativeProgress Uses

func (x *Model_TrainingRun_TrainingOptions) GetMinRelativeProgress() *wrapperspb.DoubleValue

func (*Model_TrainingRun_TrainingOptions) GetMinSplitLoss Uses

func (x *Model_TrainingRun_TrainingOptions) GetMinSplitLoss() *wrapperspb.DoubleValue

func (*Model_TrainingRun_TrainingOptions) GetModelUri Uses

func (x *Model_TrainingRun_TrainingOptions) GetModelUri() string

func (*Model_TrainingRun_TrainingOptions) GetNonSeasonalOrder Uses

func (x *Model_TrainingRun_TrainingOptions) GetNonSeasonalOrder() *Model_ArimaOrder

func (*Model_TrainingRun_TrainingOptions) GetNumClusters Uses

func (x *Model_TrainingRun_TrainingOptions) GetNumClusters() int64

func (*Model_TrainingRun_TrainingOptions) GetNumFactors Uses

func (x *Model_TrainingRun_TrainingOptions) GetNumFactors() int64

func (*Model_TrainingRun_TrainingOptions) GetOptimizationStrategy Uses

func (x *Model_TrainingRun_TrainingOptions) GetOptimizationStrategy() Model_OptimizationStrategy

func (*Model_TrainingRun_TrainingOptions) GetPreserveInputStructs Uses

func (x *Model_TrainingRun_TrainingOptions) GetPreserveInputStructs() bool

func (*Model_TrainingRun_TrainingOptions) GetSubsample Uses

func (x *Model_TrainingRun_TrainingOptions) GetSubsample() float64

func (*Model_TrainingRun_TrainingOptions) GetTimeSeriesDataColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesDataColumn() string

func (*Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumn() string

func (*Model_TrainingRun_TrainingOptions) GetTimeSeriesTimestampColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesTimestampColumn() string

func (*Model_TrainingRun_TrainingOptions) GetUserColumn Uses

func (x *Model_TrainingRun_TrainingOptions) GetUserColumn() string

func (*Model_TrainingRun_TrainingOptions) GetWalsAlpha Uses

func (x *Model_TrainingRun_TrainingOptions) GetWalsAlpha() *wrapperspb.DoubleValue

func (*Model_TrainingRun_TrainingOptions) GetWarmStart Uses

func (x *Model_TrainingRun_TrainingOptions) GetWarmStart() *wrapperspb.BoolValue

func (*Model_TrainingRun_TrainingOptions) ProtoMessage Uses

func (*Model_TrainingRun_TrainingOptions) ProtoMessage()

func (*Model_TrainingRun_TrainingOptions) ProtoReflect Uses

func (x *Model_TrainingRun_TrainingOptions) ProtoReflect() protoreflect.Message

func (*Model_TrainingRun_TrainingOptions) Reset Uses

func (x *Model_TrainingRun_TrainingOptions) Reset()

func (*Model_TrainingRun_TrainingOptions) String Uses

func (x *Model_TrainingRun_TrainingOptions) String() string

type PatchModelRequest Uses

type PatchModelRequest struct {

    // Required. Project ID of the model to patch.
    ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
    // Required. Dataset ID of the model to patch.
    DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
    // Required. Model ID of the model to patch.
    ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
    // Required. Patched model.
    // Follows RFC5789 patch semantics. Missing fields are not updated.
    // To clear a field, explicitly set to default value.
    Model *Model `protobuf:"bytes,4,opt,name=model,proto3" json:"model,omitempty"`
    // contains filtered or unexported fields
}

func (*PatchModelRequest) Descriptor Uses

func (*PatchModelRequest) Descriptor() ([]byte, []int)

Deprecated: Use PatchModelRequest.ProtoReflect.Descriptor instead.

func (*PatchModelRequest) GetDatasetId Uses

func (x *PatchModelRequest) GetDatasetId() string

func (*PatchModelRequest) GetModel Uses

func (x *PatchModelRequest) GetModel() *Model

func (*PatchModelRequest) GetModelId Uses

func (x *PatchModelRequest) GetModelId() string

func (*PatchModelRequest) GetProjectId Uses

func (x *PatchModelRequest) GetProjectId() string

func (*PatchModelRequest) ProtoMessage Uses

func (*PatchModelRequest) ProtoMessage()

func (*PatchModelRequest) ProtoReflect Uses

func (x *PatchModelRequest) ProtoReflect() protoreflect.Message

func (*PatchModelRequest) Reset Uses

func (x *PatchModelRequest) Reset()

func (*PatchModelRequest) String Uses

func (x *PatchModelRequest) String() string

type StandardSqlDataType Uses

type StandardSqlDataType struct {

    // Required. The top level type of this field.
    // Can be any standard SQL data type (e.g., "INT64", "DATE", "ARRAY").
    TypeKind StandardSqlDataType_TypeKind `protobuf:"varint,1,opt,name=type_kind,json=typeKind,proto3,enum=google.cloud.bigquery.v2.StandardSqlDataType_TypeKind" json:"type_kind,omitempty"`
    // Types that are assignable to SubType:
    //	*StandardSqlDataType_ArrayElementType
    //	*StandardSqlDataType_StructType
    SubType isStandardSqlDataType_SubType `protobuf_oneof:"sub_type"`
    // contains filtered or unexported fields
}

The type of a variable, e.g., a function argument. Examples: INT64: {type_kind="INT64"} ARRAY<STRING>: {type_kind="ARRAY", array_element_type="STRING"} STRUCT<x STRING, y ARRAY<DATE>>:

{type_kind="STRUCT",
 struct_type={fields=[
   {name="x", type={type_kind="STRING"}},
   {name="y", type={type_kind="ARRAY", array_element_type="DATE"}}
 ]}}

func (*StandardSqlDataType) Descriptor Uses

func (*StandardSqlDataType) Descriptor() ([]byte, []int)

Deprecated: Use StandardSqlDataType.ProtoReflect.Descriptor instead.

func (*StandardSqlDataType) GetArrayElementType Uses

func (x *StandardSqlDataType) GetArrayElementType() *StandardSqlDataType

func (*StandardSqlDataType) GetStructType Uses

func (x *StandardSqlDataType) GetStructType() *StandardSqlStructType

func (*StandardSqlDataType) GetSubType Uses

func (m *StandardSqlDataType) GetSubType() isStandardSqlDataType_SubType

func (*StandardSqlDataType) GetTypeKind Uses

func (x *StandardSqlDataType) GetTypeKind() StandardSqlDataType_TypeKind

func (*StandardSqlDataType) ProtoMessage Uses

func (*StandardSqlDataType) ProtoMessage()

func (*StandardSqlDataType) ProtoReflect Uses

func (x *StandardSqlDataType) ProtoReflect() protoreflect.Message

func (*StandardSqlDataType) Reset Uses

func (x *StandardSqlDataType) Reset()

func (*StandardSqlDataType) String Uses

func (x *StandardSqlDataType) String() string

type StandardSqlDataType_ArrayElementType Uses

type StandardSqlDataType_ArrayElementType struct {
    // The type of the array's elements, if type_kind = "ARRAY".
    ArrayElementType *StandardSqlDataType `protobuf:"bytes,2,opt,name=array_element_type,json=arrayElementType,proto3,oneof"`
}

type StandardSqlDataType_StructType Uses

type StandardSqlDataType_StructType struct {
    // The fields of this struct, in order, if type_kind = "STRUCT".
    StructType *StandardSqlStructType `protobuf:"bytes,3,opt,name=struct_type,json=structType,proto3,oneof"`
}

type StandardSqlDataType_TypeKind Uses

type StandardSqlDataType_TypeKind int32
const (
    // Invalid type.
    StandardSqlDataType_TYPE_KIND_UNSPECIFIED StandardSqlDataType_TypeKind = 0
    // Encoded as a string in decimal format.
    StandardSqlDataType_INT64 StandardSqlDataType_TypeKind = 2
    // Encoded as a boolean "false" or "true".
    StandardSqlDataType_BOOL StandardSqlDataType_TypeKind = 5
    // Encoded as a number, or string "NaN", "Infinity" or "-Infinity".
    StandardSqlDataType_FLOAT64 StandardSqlDataType_TypeKind = 7
    // Encoded as a string value.
    StandardSqlDataType_STRING StandardSqlDataType_TypeKind = 8
    // Encoded as a base64 string per RFC 4648, section 4.
    StandardSqlDataType_BYTES StandardSqlDataType_TypeKind = 9
    // Encoded as an RFC 3339 timestamp with mandatory "Z" time zone string:
    // 1985-04-12T23:20:50.52Z
    StandardSqlDataType_TIMESTAMP StandardSqlDataType_TypeKind = 19
    // Encoded as RFC 3339 full-date format string: 1985-04-12
    StandardSqlDataType_DATE StandardSqlDataType_TypeKind = 10
    // Encoded as RFC 3339 partial-time format string: 23:20:50.52
    StandardSqlDataType_TIME StandardSqlDataType_TypeKind = 20
    // Encoded as RFC 3339 full-date "T" partial-time: 1985-04-12T23:20:50.52
    StandardSqlDataType_DATETIME StandardSqlDataType_TypeKind = 21
    // Encoded as WKT
    StandardSqlDataType_GEOGRAPHY StandardSqlDataType_TypeKind = 22
    // Encoded as a decimal string.
    StandardSqlDataType_NUMERIC StandardSqlDataType_TypeKind = 23
    // Encoded as a decimal string.
    StandardSqlDataType_BIGNUMERIC StandardSqlDataType_TypeKind = 24
    // Encoded as a list with types matching Type.array_type.
    StandardSqlDataType_ARRAY StandardSqlDataType_TypeKind = 16
    // Encoded as a list with fields of type Type.struct_type[i]. List is used
    // because a JSON object cannot have duplicate field names.
    StandardSqlDataType_STRUCT StandardSqlDataType_TypeKind = 17
)

func (StandardSqlDataType_TypeKind) Descriptor Uses

func (StandardSqlDataType_TypeKind) Descriptor() protoreflect.EnumDescriptor

func (StandardSqlDataType_TypeKind) Enum Uses

func (x StandardSqlDataType_TypeKind) Enum() *StandardSqlDataType_TypeKind

func (StandardSqlDataType_TypeKind) EnumDescriptor Uses

func (StandardSqlDataType_TypeKind) EnumDescriptor() ([]byte, []int)

Deprecated: Use StandardSqlDataType_TypeKind.Descriptor instead.

func (StandardSqlDataType_TypeKind) Number Uses

func (x StandardSqlDataType_TypeKind) Number() protoreflect.EnumNumber

func (StandardSqlDataType_TypeKind) String Uses

func (x StandardSqlDataType_TypeKind) String() string

func (StandardSqlDataType_TypeKind) Type Uses

func (StandardSqlDataType_TypeKind) Type() protoreflect.EnumType

type StandardSqlField Uses

type StandardSqlField struct {

    // Optional. The name of this field. Can be absent for struct fields.
    Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
    // Optional. The type of this parameter. Absent if not explicitly
    // specified (e.g., CREATE FUNCTION statement can omit the return type;
    // in this case the output parameter does not have this "type" field).
    Type *StandardSqlDataType `protobuf:"bytes,2,opt,name=type,proto3" json:"type,omitempty"`
    // contains filtered or unexported fields
}

A field or a column.

func (*StandardSqlField) Descriptor Uses

func (*StandardSqlField) Descriptor() ([]byte, []int)

Deprecated: Use StandardSqlField.ProtoReflect.Descriptor instead.

func (*StandardSqlField) GetName Uses

func (x *StandardSqlField) GetName() string

func (*StandardSqlField) GetType Uses

func (x *StandardSqlField) GetType() *StandardSqlDataType

func (*StandardSqlField) ProtoMessage Uses

func (*StandardSqlField) ProtoMessage()

func (*StandardSqlField) ProtoReflect Uses

func (x *StandardSqlField) ProtoReflect() protoreflect.Message

func (*StandardSqlField) Reset Uses

func (x *StandardSqlField) Reset()

func (*StandardSqlField) String Uses

func (x *StandardSqlField) String() string

type StandardSqlStructType Uses

type StandardSqlStructType struct {
    Fields []*StandardSqlField `protobuf:"bytes,1,rep,name=fields,proto3" json:"fields,omitempty"`
    // contains filtered or unexported fields
}

func (*StandardSqlStructType) Descriptor Uses

func (*StandardSqlStructType) Descriptor() ([]byte, []int)

Deprecated: Use StandardSqlStructType.ProtoReflect.Descriptor instead.

func (*StandardSqlStructType) GetFields Uses

func (x *StandardSqlStructType) GetFields() []*StandardSqlField

func (*StandardSqlStructType) ProtoMessage Uses

func (*StandardSqlStructType) ProtoMessage()

func (*StandardSqlStructType) ProtoReflect Uses

func (x *StandardSqlStructType) ProtoReflect() protoreflect.Message

func (*StandardSqlStructType) Reset Uses

func (x *StandardSqlStructType) Reset()

func (*StandardSqlStructType) String Uses

func (x *StandardSqlStructType) String() string

type TableReference Uses

type TableReference struct {

    // Required. The ID of the project containing this table.
    ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
    // Required. The ID of the dataset containing this table.
    DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
    // Required. The ID of the table. The ID must contain only
    // letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum
    // length is 1,024 characters.  Certain operations allow
    // suffixing of the table ID with a partition decorator, such as
    // `sample_table$20190123`.
    TableId string `protobuf:"bytes,3,opt,name=table_id,json=tableId,proto3" json:"table_id,omitempty"`
    // contains filtered or unexported fields
}

func (*TableReference) Descriptor Uses

func (*TableReference) Descriptor() ([]byte, []int)

Deprecated: Use TableReference.ProtoReflect.Descriptor instead.

func (*TableReference) GetDatasetId Uses

func (x *TableReference) GetDatasetId() string

func (*TableReference) GetProjectId Uses

func (x *TableReference) GetProjectId() string

func (*TableReference) GetTableId Uses

func (x *TableReference) GetTableId() string

func (*TableReference) ProtoMessage Uses

func (*TableReference) ProtoMessage()

func (*TableReference) ProtoReflect Uses

func (x *TableReference) ProtoReflect() protoreflect.Message

func (*TableReference) Reset Uses

func (x *TableReference) Reset()

func (*TableReference) String Uses

func (x *TableReference) String() string

type UnimplementedModelServiceServer Uses

type UnimplementedModelServiceServer struct {
}

UnimplementedModelServiceServer can be embedded to have forward compatible implementations.

func (*UnimplementedModelServiceServer) DeleteModel Uses

func (*UnimplementedModelServiceServer) DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error)

func (*UnimplementedModelServiceServer) GetModel Uses

func (*UnimplementedModelServiceServer) GetModel(context.Context, *GetModelRequest) (*Model, error)

func (*UnimplementedModelServiceServer) ListModels Uses

func (*UnimplementedModelServiceServer) ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)

func (*UnimplementedModelServiceServer) PatchModel Uses

func (*UnimplementedModelServiceServer) PatchModel(context.Context, *PatchModelRequest) (*Model, error)

Package bigquery imports 13 packages (graph). Updated 2020-10-22. Refresh now. Tools for package owners.