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java.lang.Objectorg.mymedialite.data.RatingCrossValidationSplit
public class RatingCrossValidationSplit
k-fold cross-validation split for rating prediction. Please note that k-fold cross-validation is not the best/most realistic way of evaluating recommender system algorithms. In particular, chronological splits (see RatingsChronologicalSplit) are more realistic. The dataset must not be modified after the split - this would lead to undefined behavior.
Constructor Summary | |
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RatingCrossValidationSplit(IRatings ratings,
int num_folds)
Create a k-fold split of rating prediction data. |
Method Summary | |
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int |
numberOfFolds()
The number of folds in this split. |
java.util.List<IRatings> |
test()
Test data for the different folds. |
java.util.List<IRatings> |
train()
Training data for the different folds. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public RatingCrossValidationSplit(IRatings ratings, int num_folds)
ratings
- the datasetnum_folds
- the number of foldsMethod Detail |
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public int numberOfFolds()
ISplit
numberOfFolds
in interface ISplit<IRatings>
public java.util.List<IRatings> train()
ISplit
train
in interface ISplit<IRatings>
public java.util.List<IRatings> test()
ISplit
test
in interface ISplit<IRatings>
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