## Package org.apache.mahout.cf.taste.impl.eval

Class Summary
AbstractDifferenceRecommenderEvaluator: Abstract superclass of a couple implementations, providing shared functionality.
AverageAbsoluteDifferenceRecommenderEvaluator: A `RecommenderEvaluator` which computes the average absolute difference between predicted and actual ratings for users.
GenericRecommenderIRStatsEvaluator: For each user, these implementation determine the top `n` preferences, then evaluate the IR statistics based on a `DataModel` that does not have these values.
GenericRelevantItemsDataSplitter: Picks relevant items to be those with the strongest preference, and includes the other users' preferences in full.
IRStatisticsImpl
LoadEvaluator: Simple helper class for running load on a Recommender.
LoadStatistics
OrderBasedRecommenderEvaluator: Evaluate recommender by comparing order of all raw prefs with order in recommender's output for that user.
RMSRecommenderEvaluator: A `RecommenderEvaluator` which computes the "root mean squared" difference between predicted and actual ratings for users.

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