C# 클래스 MyMediaLite.Util.GridSearch

Grid search for finding suitable hyperparameters

파일 보기 프로젝트 열기: zenogantner/MML-KDD

공개 메소드들

메소드	설명
FindMinimum ( string evaluation_measure, string hyperparameter_name, double hyperparameter_values, RatingPrediction recommender, int k ) : double	Find the the parameters resulting in the minimal results for a given evaluation measure using k-fold cross-validation The recommender will be set to the best parameter value after calling this method.
FindMinimum ( string evaluation_measure, string hyperparameter_name, double hyperparameter_values, RatingPredictor recommender, ISplit split ) : double	Find the the parameters resulting in the minimal results for a given evaluation measure (1D) The recommender will be set to the best parameter value after calling this method.
FindMinimum ( string evaluation_measure, string hp_name1, string hp_name2, double hp_values1, double hp_values2, RatingPredictor recommender, ISplit split ) : double	Find the the parameters resulting in the minimal results for a given evaluation measure (2D) The recommender will be set to the best parameter value after calling this method.
FindMinimumExponential ( string evaluation_measure, string hp_name, double hp_values, double basis, RatingPrediction recommender, ISplit split ) : double	Find the the parameters resulting in the minimal results for a given evaluation measure (1D) The recommender will be set to the best parameter value after calling this method.
FindMinimumExponential ( string evaluation_measure, string hp_name1, string hp_name2, double hp_values1, double hp_values2, double basis, RatingPrediction recommender, ISplit split ) : double	Find the the parameters resulting in the minimal results for a given evaluation measure (2D) The recommender will be set to the best parameter value after calling this method.

메소드 상세

FindMinimum() 공개 정적인 메소드

Find the the parameters resulting in the minimal results for a given evaluation measure using k-fold cross-validation

The recommender will be set to the best parameter value after calling this method.

public static FindMinimum ( string evaluation_measure, string hyperparameter_name, double hyperparameter_values, RatingPrediction recommender, int k ) : double
evaluation_measure	string	the name of the evaluation measure
hyperparameter_name	string	the name of the hyperparameter to optimize
hyperparameter_values	double	the values of the hyperparameter to try out
recommender	RatingPrediction	the recommender
k	int	the number of folds to be used for cross-validation
리턴	double

FindMinimum() 공개 정적인 메소드

Find the the parameters resulting in the minimal results for a given evaluation measure (1D)

The recommender will be set to the best parameter value after calling this method.

public static FindMinimum ( string evaluation_measure, string hyperparameter_name, double hyperparameter_values, RatingPredictor recommender, ISplit split ) : double
evaluation_measure	string	the name of the evaluation measure
hyperparameter_name	string	the name of the hyperparameter to optimize
hyperparameter_values	double	the values of the hyperparameter to try out
recommender	MyMediaLite.RatingPrediction.RatingPredictor	the recommender
split	ISplit	the dataset split to use
리턴	double

FindMinimum() 공개 정적인 메소드

Find the the parameters resulting in the minimal results for a given evaluation measure (2D)

The recommender will be set to the best parameter value after calling this method.

public static FindMinimum ( string evaluation_measure, string hp_name1, string hp_name2, double hp_values1, double hp_values2, RatingPredictor recommender, ISplit split ) : double
evaluation_measure	string	the name of the evaluation measure
hp_name1	string	the name of the first hyperparameter to optimize
hp_name2	string	the name of the second hyperparameter to optimize
hp_values1	double	the values of the first hyperparameter to try out
hp_values2	double	the values of the second hyperparameter to try out
recommender	MyMediaLite.RatingPrediction.RatingPredictor	the recommender
split	ISplit	the dataset split to use
리턴	double

FindMinimumExponential() 공개 정적인 메소드

Find the the parameters resulting in the minimal results for a given evaluation measure (1D)

The recommender will be set to the best parameter value after calling this method.

public static FindMinimumExponential ( string evaluation_measure, string hp_name, double hp_values, double basis, RatingPrediction recommender, ISplit split ) : double
evaluation_measure	string	the name of the evaluation measure
hp_name	string	the name of the hyperparameter to optimize
hp_values	double	the logarithms of the values of the hyperparameter to try out
basis	double	the basis to use for the logarithms
recommender	RatingPrediction	the recommender
split	ISplit	the dataset split to use
리턴	double

FindMinimumExponential() 공개 정적인 메소드

Find the the parameters resulting in the minimal results for a given evaluation measure (2D)

The recommender will be set to the best parameter value after calling this method.

public static FindMinimumExponential ( string evaluation_measure, string hp_name1, string hp_name2, double hp_values1, double hp_values2, double basis, RatingPrediction recommender, ISplit split ) : double
evaluation_measure	string	the name of the evaluation measure
hp_name1	string	the name of the first hyperparameter to optimize
hp_name2	string	the name of the second hyperparameter to optimize
hp_values1	double	the logarithm values of the first hyperparameter to try out
hp_values2	double	the logarithm values of the second hyperparameter to try out
basis	double	the basis to use for the logarithms
recommender	RatingPrediction	the recommender
split	ISplit	the dataset split to use
리턴	double