prea.data.preparation
Class KfoldCrossValidation

java.lang.Object
  extended by prea.data.preparation.DatasetManager
      extended by prea.data.preparation.KfoldCrossValidation

public class KfoldCrossValidation
extends DatasetManager

This class implements K-fold cross-validation.

Since:
2012. 3. 26
Version:
1.1
Author:
Joonseok Lee

Field Summary
private  SparseMatrix assign
           
private  int foldCount
           
 
Fields inherited from class prea.data.preparation.DatasetManager
itemCount, itemRateAverage, K_FOLD_CROSS_VALIDATION, maxValue, minValue, PREDEFINED_SPLIT, rateMatrix, SIMPLE_SPLIT, testMatrix, userCount, userRateAverage
 
Constructor Summary
KfoldCrossValidation(SparseMatrix originalMatrix, int k, int max, int min)
          Construct an instance for K-fold cross-validation.
 
Method Summary
private  void divideFolds(int k)
          Divide the original rating matrix into k-fold.
 SparseMatrix getKthFold(int k)
          Return the k-th fold as test set (testMatrix), making all the others as train set in rateMatrix.
 
Methods inherited from class prea.data.preparation.DatasetManager
calculateAverage, getItemRateAverage, getTestMatrix, getUserRateAverage, recoverTestItems
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

assign

private SparseMatrix assign

foldCount

private int foldCount
Constructor Detail

KfoldCrossValidation

public KfoldCrossValidation(SparseMatrix originalMatrix,
                            int k,
                            int max,
                            int min)
Construct an instance for K-fold cross-validation.

Method Detail

divideFolds

private void divideFolds(int k)
Divide the original rating matrix into k-fold. Illegal k would be adjusted automatically.

Parameters:
k - The index for desired fold.

getKthFold

public SparseMatrix getKthFold(int k)
Return the k-th fold as test set (testMatrix), making all the others as train set in rateMatrix.

Parameters:
k - The index for desired fold.
Returns:
Rating matrix with test data with data points in k-th fold.