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## E

estimation(int, int, int[], int, double[], int) - Method in class prea.recommender.memory.ItemBased
  Estimate a rating based on neighborhood data.
estimation(int, int, int[], int, double[], int) - Method in class prea.recommender.memory.UserBased
  Estimate a rating based on neighborhood data.
evaluate(SparseMatrix) - Method in class prea.recommender.baseline.BaselineRecommender
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.CustomRecommender
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.etc.FastNPCA
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.etc.NonlinearPMF
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.etc.RankBased
  Evaluate the rank-based CF algorithm with the given probabilites and loss function.
evaluate(SparseMatrix) - Method in class prea.recommender.etc.SlopeOne
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.matrix.MatrixFactorizationRecommender
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.memory.ItemBased
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in class prea.recommender.memory.UserBased
  Evaluate the designated algorithm with the given test data.
evaluate(SparseMatrix) - Method in interface prea.recommender.Recommender
  Interface of evaluation method.
EvaluationMetrics - Class in prea.util
  This is a unified class providing evaluation metrics, including comparison of predicted ratings and rank-based metrics, etc.
EvaluationMetrics(SparseMatrix, SparseMatrix, double, double) - Constructor for class prea.util.EvaluationMetrics
  Standard constructor for EvaluationMetrics class.
evaluationMode - Static variable in class prea.main.Prea
  Evaluation mode
exp(double) - Method in class prea.data.structure.DenseMatrix
  Exponential of a given constant.
exp(double) - Method in class prea.data.structure.DenseVector
  Exponential of a given constant.
exp(double) - Method in class prea.data.structure.SparseMatrix
  Exponential of a given constant.
exp(double) - Method in class prea.data.structure.SparseVector
  Exponential of a given constant.
expTransform(DenseVector, int) - Method in class prea.recommender.etc.NonlinearPMF
  Transform a vector by log function, exponential function or linear function.

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