Uses of Class
prea.util.EvaluationMetrics

Packages that use EvaluationMetrics
prea.recommender   
prea.recommender.baseline   
prea.recommender.etc   
prea.recommender.matrix   
prea.recommender.memory   
 

Uses of EvaluationMetrics in prea.recommender
 

Methods in prea.recommender that return EvaluationMetrics
 EvaluationMetrics Recommender.evaluate(SparseMatrix tm)
          Interface of evaluation method.
 EvaluationMetrics CustomRecommender.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 

Uses of EvaluationMetrics in prea.recommender.baseline
 

Methods in prea.recommender.baseline that return EvaluationMetrics
 EvaluationMetrics BaselineRecommender.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 

Uses of EvaluationMetrics in prea.recommender.etc
 

Methods in prea.recommender.etc that return EvaluationMetrics
 EvaluationMetrics SlopeOne.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 EvaluationMetrics RankBased.evaluate(SparseMatrix testMatrix)
          Evaluate the rank-based CF algorithm with the given probabilites and loss function.
 EvaluationMetrics NonlinearPMF.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 EvaluationMetrics FastNPCA.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 

Uses of EvaluationMetrics in prea.recommender.matrix
 

Methods in prea.recommender.matrix that return EvaluationMetrics
 EvaluationMetrics MatrixFactorizationRecommender.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 

Uses of EvaluationMetrics in prea.recommender.memory
 

Methods in prea.recommender.memory that return EvaluationMetrics
 EvaluationMetrics UserBased.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.
 EvaluationMetrics ItemBased.evaluate(SparseMatrix testMatrix)
          Evaluate the designated algorithm with the given test data.