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java.lang.Objectorg.mymedialite.hyperparameter.GridSearch
public class GridSearch
Grid search for finding suitable hyperparameters.
Method Summary | |
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static double |
findMinimum(java.lang.String evaluation_measure,
java.lang.String hyperparameter_name,
double[] hyperparameter_values,
RatingPredictor recommender,
int k)
Find the the parameters resulting in the minimal results for a given evaluation measure using k-fold cross-validation. |
static double |
findMinimum(java.lang.String evaluation_measure,
java.lang.String hyperparameter_name,
double[] hyperparameter_values,
RatingPredictor recommender,
ISplit<IRatings> split)
Find the the parameters resulting in the minimal results for a given evaluation measure (1D). |
static double |
findMinimum(java.lang.String evaluation_measure,
java.lang.String hp_name1,
java.lang.String hp_name2,
double[] hp_values1,
double[] hp_values2,
RatingPredictor recommender,
ISplit<IRatings> split)
Find the the parameters resulting in the minimal results for a given evaluation measure (2D). |
static double |
findMinimumExponential(java.lang.String evaluation_measure,
java.lang.String hp_name,
double[] hp_values,
double basis,
RatingPredictor recommender,
ISplit<IRatings> split)
Find the the parameters resulting in the minimal results for a given evaluation measure (1D). |
static double |
findMinimumExponential(java.lang.String evaluation_measure,
java.lang.String hp_name1,
java.lang.String hp_name2,
double[] hp_values1,
double[] hp_values2,
double basis,
RatingPredictor recommender,
ISplit<IRatings> split)
Find the the parameters resulting in the minimal results for a given evaluation measure (2D). |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Method Detail |
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public static double findMinimum(java.lang.String evaluation_measure, java.lang.String hyperparameter_name, double[] hyperparameter_values, RatingPredictor recommender, ISplit<IRatings> split) throws java.lang.Exception
evaluation_measure
- the name of the evaluation measurehyperparameter_name
- the name of the hyperparameter to optimizehyperparameter_values
- the values of the hyperparameter to try outrecommender
- the recommendersplit
- the dataset split to use
java.lang.Exception
public static double findMinimum(java.lang.String evaluation_measure, java.lang.String hp_name1, java.lang.String hp_name2, double[] hp_values1, double[] hp_values2, RatingPredictor recommender, ISplit<IRatings> split) throws java.lang.Exception
evaluation_measure
- the name of the evaluation measurehp_name1
- the name of the first hyperparameter to optimizehp_values1
- the values of the first hyperparameter to try outhp_name2
- the name of the second hyperparameter to optimizehp_values2
- the values of the second hyperparameter to try outrecommender
- the recommendersplit
- the dataset split to use
java.lang.Exception
public static double findMinimumExponential(java.lang.String evaluation_measure, java.lang.String hp_name1, java.lang.String hp_name2, double[] hp_values1, double[] hp_values2, double basis, RatingPredictor recommender, ISplit<IRatings> split) throws java.lang.Exception
evaluation_measure
- the name of the evaluation measurehp_name1
- the name of the first hyperparameter to optimizehp_values1
- the logarithm values of the first hyperparameter to try outhp_name2
- the name of the second hyperparameter to optimizehp_values2
- the logarithm values of the second hyperparameter to try outbasis
- the basis to use for the logarithmsrecommender
- the recommendersplit
- the dataset split to use
java.lang.Exception
public static double findMinimumExponential(java.lang.String evaluation_measure, java.lang.String hp_name, double[] hp_values, double basis, RatingPredictor recommender, ISplit<IRatings> split) throws java.lang.Exception
evaluation_measure
- the name of the evaluation measurehp_name
- the name of the hyperparameter to optimizehp_values
- the logarithms of the values of the hyperparameter to try outbasis
- the basis to use for the logarithmsrecommender
- the recommendersplit
- the dataset split to use
java.lang.Exception
public static double findMinimum(java.lang.String evaluation_measure, java.lang.String hyperparameter_name, double[] hyperparameter_values, RatingPredictor recommender, int k) throws java.lang.Exception
evaluation_measure
- the name of the evaluation measurehyperparameter_name
- the name of the hyperparameter to optimizehyperparameter_values
- the values of the hyperparameter to try outrecommender
- the recommenderk
- the number of folds to be used for cross-validation
java.lang.Exception
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