Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES

## Uses of Interface
prea.recommender.Recommender

Packages that use Recommender
prea.main |
prea.recommender |
prea.recommender.baseline |
prea.recommender.etc |
prea.recommender.matrix |
prea.recommender.memory |

Uses of Recommender in prea.main

Methods in prea.main with parameters of type Recommender
`static java.lang.String` | `Prea.testRecommender(java.lang.String algorithmName, Recommender r)` Test interface for a recommender system.

Uses of Recommender in prea.recommender

Classes in prea.recommender that implement Recommender
`class` | `CustomRecommender` This is a skeleton class for user-defined custom recommenders.

Fields in prea.recommender declared as Recommender
`private Recommender` | `UnitTest.targetRecommender`

Constructors in prea.recommender with parameters of type Recommender
`UnitTest(Recommender r, SparseMatrix rm, SparseMatrix tm)` Construct an instance of unit test module.

Uses of Recommender in prea.recommender.baseline

Classes in prea.recommender.baseline that implement Recommender
`class` | `Average` The class implementing a baseline, predicting by overall average of training set ratings.
`class` | `BaselineRecommender` This is an abstract class implementing five baselines, including constant model, overall average, user average, item average, and random.
`class` | `Constant` The class implementing a baseline, always predicting with the given constant.
`class` | `ItemAverage` The class implementing a baseline, predicting by the average of target item ratings.
`class` | `Random` The class implementing a baseline, predicting uniformly randomly from the score range.
`class` | `UserAverage` The class implementing a baseline, predicting by the average of target user ratings.

Uses of Recommender in prea.recommender.etc

Classes in prea.recommender.etc that implement Recommender
`class` | `FastNPCA` This is a class implementing Fast Nonparametric Principal Component Analysis (NPCA).
`class` | `NonlinearPMF` This is a class implementing Non-linear Probabilistic Matrix Factorization.
`class` | `RankBased` This is a class implementing rank-based collaborative filtering.
`class` | `SlopeOne` This is a class implementing Slope-One algorithm.

Uses of Recommender in prea.recommender.matrix

Classes in prea.recommender.matrix that implement Recommender
`class` | `BayesianPMF` This is a class implementing Bayesian Probabilistic Matrix Factorization.
`class` | `MatrixFactorizationRecommender` This is an abstract class implementing four matrix-factorization-based methods including Regularized SVD, NMF, PMF, and Bayesian PMF.
`class` | `NMF` This is a class implementing Non-negative Matrix Factorization.
`class` | `PMF` This is a class implementing Probabilistic Matrix Factorization.
`class` | `RegularizedSVD` This is a class implementing Regularized SVD (Singular Value Decomposition).

Uses of Recommender in prea.recommender.memory

Classes in prea.recommender.memory that implement Recommender
`class` | `ItemBased` The class implementing item-based neighborhood method, predicting by referring to rating matrix for each query.
`class` | `MemoryBasedRecommender` The class implementing two memory-based (neighborhood-based) methods, predicting by referring to rating matrix for each query.
`class` | `UserBased` The class implementing user-based neighborhood method, predicting by referring to rating matrix for each query.

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES