Documentation
¶
Index ¶
- Variables
- func LocateBuiltInDataset(name string, format DatasetFormat) (string, string, error)
- type BaseModel
- type DatasetFormat
- type Model
- type ParamName
- type Params
- func (parameters Params) Copy() Params
- func (parameters Params) GetBool(name ParamName, _default bool) bool
- func (parameters Params) GetFloat32(name ParamName, _default float32) float32
- func (parameters Params) GetInt(name ParamName, _default int) int
- func (parameters Params) GetInt64(name ParamName, _default int64) int64
- func (parameters Params) GetString(name ParamName, _default string) string
- func (parameters Params) Overwrite(params Params) Params
- func (parameters Params) ToString() string
- type ParamsGrid
Constants ¶
This section is empty.
Variables ¶
var ( GorseDir string DataSetDir string TempDir string )
The Data directories
Functions ¶
func LocateBuiltInDataset ¶ added in v0.2.0
func LocateBuiltInDataset(name string, format DatasetFormat) (string, string, error)
Types ¶
type BaseModel ¶ added in v0.2.0
type BaseModel struct {
Params Params // Hyper-parameters
// contains filtered or unexported fields
}
BaseModel model must be included by every recommendation model. Hyper-parameters, ID sets, random generator and fitting options are managed the BaseModel model.
func (*BaseModel) GetRandomGenerator ¶ added in v0.2.0
func (model *BaseModel) GetRandomGenerator() base.RandomGenerator
type DatasetFormat ¶ added in v0.2.0
type DatasetFormat int
const ( FormatNCF DatasetFormat = iota FormatLibFM )
type Model ¶ added in v0.2.0
type Model interface {
SetParams(params Params)
GetParams() Params
GetParamsGrid(withSize bool) ParamsGrid
Clear()
Invalid() bool
}
Model is the interface for all models. Any model in this package should implement it.
type ParamName ¶ added in v0.2.0
type ParamName string
ParamName is the type of hyper-parameter names.
const ( Lr ParamName = "Lr" // learning rate Reg ParamName = "Reg" // regularization strength NEpochs ParamName = "NEpochs" // number of epochs NFactors ParamName = "NFactors" // number of factors RandomState ParamName = "RandomState" // random state (seed) InitMean ParamName = "InitMean" // mean of gaussian initial parameter InitStdDev ParamName = "InitStdDev" // standard deviation of gaussian initial parameter Alpha ParamName = "Alpha" // weight for negative samples in ALS Similarity ParamName = "Similarity" UseFeature ParamName = "UseFeature" )
Predefined hyper-parameter names
type Params ¶ added in v0.2.0
type Params map[ParamName]interface{}
Params stores hyper-parameters for an model. It is a map between strings (names) and interface{}s (values). For example, hyper-parameters for SVD is given by:
base.Params{
base.Lr: 0.007,
base.NEpochs: 100,
base.NFactors: 80,
base.Reg: 0.1,
}
func (Params) GetBool ¶ added in v0.2.2
GetBool gets a boolean parameter by name. Returns _default if not exists or type doesn't match.
func (Params) GetFloat32 ¶ added in v0.2.0
func (Params) GetInt ¶ added in v0.2.0
GetInt gets a integer parameter by name. Returns _default if not exists or type doesn't match.
func (Params) GetInt64 ¶ added in v0.2.0
GetInt64 gets a int64 parameter by name. Returns _default if not exists or type doesn't match. The type will be converted if given int.
type ParamsGrid ¶ added in v0.2.0
type ParamsGrid map[ParamName][]interface{}
ParamsGrid contains candidate for grid search.
func (ParamsGrid) Fill ¶ added in v0.2.0
func (grid ParamsGrid) Fill(_default ParamsGrid)
func (ParamsGrid) Len ¶ added in v0.2.0
func (grid ParamsGrid) Len() int
func (ParamsGrid) NumCombinations ¶ added in v0.2.0
func (grid ParamsGrid) NumCombinations() int
Source Files
Directories