Package es.upm.etsisi.cf4j.qualityMeasure.prediction

Contains the implementation of different quality measures oriented to predictions.

Class Summary

Class	Description
Coverage	This class calculates the Coverage of the recommender system.
MAE	This class calculates the Mean Absolute Error (MAE) between the predictions and the test ratings.
Max	This class calculates the averaged maximum prediction absolute error in a the prediction of a test rating for each test user.
MSE	This class calculates the Mean Squared Error (MSE) between the predictions and the test ratings.
MSLE	This class calculates the Mean Squared Logarithmic Error (MSLE) between the predictions and the test ratings.
Perfect	This class calculates the percentage of perfect predictions.
R2	This class calculates the the coefficient of determination, usually denoted as R2, of the predictions performed by a recommender.
RMSE	This class calculates the Root Mean Squared Error (RMSE) between the predictions and the test ratings.