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| 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. |
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| 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. |
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