Documentation ¶
Overview ¶
Package hector is a golang based machine learning lib. It intend to implement all famous machine learning algoirhtms by golang. Currently, it only support algorithms which can solve binary classification problems. Supported algorithms include: 1. Decision Tree (CART, Random Forest, GBDT) 2. Logistic Regression 3. SVM 4. Neural Network
Package hector is a golang based machine learning lib. It intend to implement all famous machine learning algoirhtms by golang. Currently, it only support algorithms which can solve binary classification problems. Supported algorithms include: 1. Decision Tree (CART, Random Forest, GBDT) 2. Logistic Regression 3. SVM 4. Neural Network
Index ¶
- func AlgorithmRun(classifier algo.Classifier, train_path string, test_path string, ...) (float64, []*eval.LabelPrediction, error)
- func AlgorithmRunOnDataSet(classifier algo.Classifier, train_dataset, test_dataset *core.DataSet, ...) (float64, []*eval.LabelPrediction)
- func AlgorithmTest(classifier algo.Classifier, test_path string, pred_path string, ...) (float64, []*eval.LabelPrediction, error)
- func AlgorithmTrain(classifier algo.Classifier, train_path string, params map[string]string) error
- func GetClassifier(method string) algo.Classifier
- func GetMutliClassClassifier(method string) algo.MultiClassClassifier
- func GetRegressor(method string) algo.Regressor
- func MultiClassRun(classifier algo.MultiClassClassifier, train_path string, test_path string, ...) (float64, error)
- func MultiClassRunOnDataSet(classifier algo.MultiClassClassifier, ...) float64
- func MultiClassTest(classifier algo.MultiClassClassifier, test_path string, pred_path string, ...) (float64, error)
- func MultiClassTrain(classifier algo.MultiClassClassifier, train_path string, ...) error
- func PrepareParams() (string, string, string, string, map[string]string)
- func RegAlgorithmRun(regressor algo.Regressor, train_path string, test_path string, ...) (float64, []*eval.RealPrediction, error)
- func RegAlgorithmRunOnDataSet(regressor algo.Regressor, train_dataset, test_dataset *core.RealDataSet, ...) (float64, []*eval.RealPrediction)
- func RegAlgorithmTest(regressor algo.Regressor, test_path string, pred_path string, ...) (float64, []*eval.RealPrediction, error)
- func RegAlgorithmTrain(regressor algo.Regressor, train_path string, params map[string]string) error
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func AlgorithmRun ¶
func AlgorithmRunOnDataSet ¶
func AlgorithmRunOnDataSet(classifier algo.Classifier, train_dataset, test_dataset *core.DataSet, pred_path string, params map[string]string) (float64, []*eval.LabelPrediction)
func AlgorithmTest ¶
func AlgorithmTest(classifier algo.Classifier, test_path string, pred_path string, params map[string]string) (float64, []*eval.LabelPrediction, error)
func AlgorithmTrain ¶
func GetClassifier ¶
func GetClassifier(method string) algo.Classifier
func GetMutliClassClassifier ¶
func GetMutliClassClassifier(method string) algo.MultiClassClassifier
func GetRegressor ¶
func MultiClassRun ¶
func MultiClassRunOnDataSet ¶
func MultiClassTest ¶
func MultiClassTrain ¶
func RegAlgorithmRun ¶
func RegAlgorithmRun(regressor algo.Regressor, train_path string, test_path string, pred_path string, params map[string]string) (float64, []*eval.RealPrediction, error)
Regression
func RegAlgorithmRunOnDataSet ¶
func RegAlgorithmRunOnDataSet(regressor algo.Regressor, train_dataset, test_dataset *core.RealDataSet, pred_path string, params map[string]string) (float64, []*eval.RealPrediction)
func RegAlgorithmTest ¶
Types ¶
This section is empty.