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## C

calculateAverage(double) - Method in class prea.data.splitter.DataSplitManager
  Calculate average of ratings for each user and each item.
changePermutationIndex(int[], int[]) - Static method in class prea.util.Distance
  Given two permutation, re-index the id to the set {1,2,.., n}, where n is the total items of the two permutations.
check() - Method in class prea.recommender.UnitTest
  Verify whether the recommender implemented correctly. 1) Check whether the recommender illegally alters train data. 2) Check whether the recommender illegally alters test data. 3) Compare to several baselines, which should beat in general.
cholesky() - Method in class prea.data.structure.DenseMatrix
  Calculate Cholesky decomposition of the matrix.
cholesky() - Method in class prea.data.structure.SparseMatrix
  Calculate Cholesky decomposition of the matrix.
collabLogLikeGradients(int, DenseVector, double, double) - Method in class prea.recommender.etc.NonlinearPMF
  Compute the gradients of the model (latent factors and kernel parameters) given one users ratings.
cols - Variable in class prea.data.structure.SparseMatrix
  The array of column references.
columnName - Static variable in class prea.main.Prea
  The list of item names, provided with the dataset.
columnName - Static variable in class prea.main.Splitter
  The list of item names, provided with the dataset.
commonMinus(DenseVector) - Method in class prea.data.structure.DenseVector
  Vector subtraction (a - b), for only existing values.
commonMinus(SparseVector) - Method in class prea.data.structure.SparseVector
  Vector subtraction (a - b), for only existing values.
computeAverageRank(double[], double[]) - Static method in class prea.util.Distance
  Return the average rank of each score with/without ties prb=(lowrank+(tie-1)/2)/(k+1)
Constant - Class in prea.recommender.baseline
  The class implementing a baseline, always predicting with the given constant.
Constant(int, int, double, double, double) - Constructor for class prea.recommender.baseline.Constant
  Construct a constant model with the given data.
constantValue - Variable in class prea.recommender.baseline.Average
  The value which will be used for predicting all ratings.
constantValue - Variable in class prea.recommender.baseline.Constant
  The value which will be used for predicting all ratings.
constructProbability() - Method in class prea.recommender.etc.RankBased
  Construct the probability (average rank) structure for each user's ranking.
constructTie() - Method in class prea.recommender.etc.RankBased
  Construct the tie structure for each user's ranking.
contains(Key) - Method in class prea.data.structure.DataMap
  Check whether the map has a specific key inside it.
copy() - Method in class prea.data.structure.DenseVector
  Copy the whole dense vector and make a clone.
copy() - Method in class prea.data.structure.SparseVector
  Copy the whole sparse vector and make a clone.
covariance() - Method in class prea.data.structure.DenseMatrix
  Generate a covariance matrix of the current matrix.
covariance() - Method in class prea.data.structure.SparseMatrix
  Generate a covariance matrix of the current matrix.
CustomRecommender - Class in prea.recommender
  This is a skeleton class for user-defined custom recommenders.
CustomRecommender(int, int, double, double) - Constructor for class prea.recommender.CustomRecommender
  Construct a customized recommender model with the given data.

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