 MyMediaLite | |
  Correlation | This namespace contains several correlation/distance measures |
   AsymmetricCorrelationMatrix | Class for computing and storing correlations and similarities |
   BidirectionalConditionalProbability | Class for storing and computing 'bi-directional' conditional probabilities |
   BinaryCosine | Class for storing cosine similarities |
   BinaryDataAsymmetricCorrelationMatrix | Class with commoin routines for asymmetric correlations that are learned from binary data |
   BinaryDataSymmetricCorrelationMatrix | Class with common routines for symmetric correlations that are learned from binary data |
   ConditionalProbability | Class for storing and computing conditional probabilities |
   Cooccurrence | Class for storing and computing the co-counts |
   Extensions | Extension methods for correlation matrices |
   IBinaryDataCorrelationMatrix | CorrelationMatrix that computes correlations over binary data |
   ICorrelationMatrix | Interface representing correlation and similarity matrices |
   IRatingCorrelationMatrix | CorrelationMatrix that computes correlations over rating data |
   Jaccard | Class for storing and computing the Jaccard index (Tanimoto coefficient) |
   Overlap | Class containing routines for computing overlaps |
   Pearson | Shrunk Pearson correlation for rating data |
   SymmetricCorrelationMatrix | Class for computing and storing correlations and similarities |
  Data | This namespace contains MyMediaLite's principal data structures, which are used e.g. to store the interaction data that is used to train personalized recommenders |
   CombinedRatings | Combine two IRatings objects |
   DataSet | Abstract dataset class that implements some common functions |
   Extensions | Extension methods for dataset statistics |
   IDataSet | Interface for different kinds of collaborative filtering data sets |
   IdentityMapping | Identity mapping for entity IDs: Every original ID is mapped to itself |
   IMapping | Interface to map external entity IDs to internal ones to ensure that there are no gaps in the numbering |
   IPosOnlyFeedback | Interface for implicit, positive-only user feedback |
   IRatings | Interface for rating datasets |
   ISplit | generic dataset splitter interface |
   ITimedDataSet | interface for data sets with time information |
   ITimedRatings | Interface for rating datasets with time information |
   KDDCupItems | Represents KDD Cup 2011 items like album, track, artist, or genre |
   Mapping | Class to map external entity IDs to internal ones to ensure that there are no gaps in the numbering |
   PosOnlyFeedback | Data structure for implicit, positive-only user feedback |
   PosOnlyFeedbackCrossValidationSplit | K-fold cross-validation split for item prediction from implicit feedback |
   PosOnlyFeedbackSimpleSplit | simple split for item prediction from implicit feedback |
   RatingCrossValidationSplit | k-fold cross-validation split for rating prediction |
   Ratings | Data structure for storing ratings |
   RatingScale | Class containing information about the rating scale of a data set: valid rating values, minimum/maximum rating. |
   RatingsChronologicalSplit | chronological split for rating prediction |
   RatingsPerUserChronologicalSplit | per-user chronological split for rating prediction |
   RatingsProxy | Data structure that allows access to selected entries of a rating data structure |
   RatingsSimpleSplit | simple split for rating prediction |
   StaticByteRatings | Array-based storage for rating data. |
   StaticRatings | Array-based storage for rating data. |
   TimedRatings | Data structure for storing ratings with time information |
   TimedRatingsProxy | Data structure that allows access to selected entries of a timed rating data structure |
  DataType | This namespace contains standard data types that are used by MyMediaLite, e.g. matrices, vectors, etc |
   CombinedList | Combines two List objects |
   IBooleanMatrix | Interface for boolean matrices |
   IMatrix | Generic interface for matrix data types |
   ListProxy | Proxy class that allows access to selected elements of an underlying list data structure |
   Matrix | Class for storing dense matrices |
   MatrixExtensions | Utilities to work with matrices |
   SkewSymmetricSparseMatrix | a skew symmetric (anti-symmetric) sparse matrix; consumes less memory |
   SparseBooleanMatrix | Sparse representation of a boolean matrix, using HashSets |
   SparseMatrix | Class for storing sparse matrices |
   SparseMatrixExtensions | Utilities to work with matrices |
   SymmetricMatrix | Class for storing dense matrices |
   SymmetricSparseMatrix | a symmetric sparse matrix; consumes less memory |
   VectorExtensions | Extensions for vector-like data |
  Diversification | This namespace contains methods for diversifying result lists |
   SequentialDiversification | Sequential diversification |
  Ensemble | This namespace contains recommender ensembles |
   Ensemble | Abtract class for combining several prediction methods |
   WeightedEnsemble | Combining several predictors with a weighted ensemble |
  Eval | This namespace contains evaluation routines |
   Measures | This namespace contains different evaluation measures |
    AUC | Area under the ROC curve (AUC) of a list of ranked items |
    LogisticLoss | Utility functions for the logistic loss |
    MAE | Utility functions for the mean absolute error |
    NDCG | Normalized discounted cumulative gain (NDCG) of a list of ranked items |
    PrecisionAndRecall | Precision and recall at different positions in the list |
    ReciprocalRank | The reciprocal rank of a list of ranked items |
    RMSE | Utility functions for the root mean square error (RMSE) |
   EvaluationResults | Class for representing evaluation results |
   FoldIn | Fold-in evaluation |
   ItemRecommendationEvaluationResults | Item recommendation evaluation results |
   Items | Evaluation class for item recommendation |
   ItemsCrossValidation | Cross-validation for item recommendation |
   ItemsOnline | Online evaluation for rankings of items |
   RatingBasedRankingCrossValidation | Cross-validation for rating-based ranking |
   RatingPredictionEvaluationResults | Rating prediction evaluation results |
   Ratings | Evaluation class for rating prediction |
   RatingsCrossValidation | Cross-validation for rating prediction |
   RatingsOnline | Online evaluation for rating prediction |
  HyperParameter | This namespace contains classes for automated hyper-parameter search |
   GridSearch | Grid search for finding suitable hyperparameters |
   IHyperParameterSearch | Interface for classes that perform hyper-parameter search |
   NelderMead | Nealder-Mead algorithm for finding suitable hyperparameters |
  IO | This namespace contains I/O routines, e.g. to load interaction data from files and databases, or for loading recommender models from disk |
   KDDCup2011 | |
    Items | Routines for reading in the item taxonomy of the KDD Cup 2011 data |
    Ratings | Class that offers static methods for reading in rating data from the KDD Cup 2011 files |
    Track2Items | Class that offers static methods for reading in test data from the KDD Cup 2011 files |
   AttributeData | Class that offers static methods to read (binary) attribute data into IBooleanMatrix objects |
   Constants | Static class containing constants used by the MyMediaLite Input/Output routines |
   DataReaderExtensions | Extension methods for IDataReader objects |
   EntityMappingExtensions | I/O routines for classes implementing the IEntityMapping interface |
   FileSerializer | Static class for serializing objects to binary files |
   FileSystem | File-system related helper functions |
   ItemData | Class that contains static methods for reading in implicit feedback data for ItemRecommender |
   ItemDataRatingThreshold | Class that contains static methods for reading in implicit feedback data for ItemRecommender, derived from rating data |
   MatrixExtensions | Utilities to work with matrices |
   Model | Class containing static routines for reading and writing recommender models |
   MovieLensRatingData | Class that offers static methods for reading in MovieLens 1M and 10M rating data |
   RatingData | Class that offers methods for reading in rating data |
   RelationData | Class that offers static methods to read (binary) relation over entities into IBooleanMatrix objects |
   StaticRatingData | Class that offers methods for reading in static rating data |
   TimedRatingData | Class that offers methods for reading in rating data with time information |
   VectorExtensions | Extensions for vector-like data |
  ItemRecommendation | This namespace contains item recommenders and some helper classes for item recommendation |
   BPRLinear | Linear model optimized for BPR |
   BPRMF | Matrix factorization model for item prediction (ranking) optimized for BPR |
   BPRSLIM | Sparse Linear Methods (SLIM) for item prediction (ranking) optimized for BPR-Opt optimization criterion |
   Extensions | Class that contains static methods for item prediction |
   ExternalItemRecommender | Uses externally computed predictions |
   IFoldInItemRecommender | Item recommender that allows folding in new users |
   IIncrementalItemRecommender | Interface for item recommenders |
   IncrementalItemRecommender | Base class for item recommenders that support incremental updates |
   ItemAttributeKNN | k-nearest neighbor (kNN) item-based collaborative filtering using the correlation of the item attibutes |
   ItemKNN | k-nearest neighbor (kNN) item-based collaborative filtering |
   ItemRecommender | Abstract item recommender class that loads the (positive-only implicit feedback) training data into memory and provides flexible access to it. |
   ITransductiveItemRecommender | Interface for item recommenders that take into account some test data for training |
   KNN | Base class for item recommenders that use some kind of k-nearest neighbors (kNN) model |
   LeastSquareSLIM | Sparse Linear Methods (SLIM) for item prediction (ranking) optimized for the elastic net loss |
   MF | Abstract class for matrix factorization based item predictors |
   MostPopular | Most-popular item recommender |
   MostPopularByAttributes | Recommend most popular items by attribute |
   MultiCoreBPRMF | Matrix factorization for BPR on multiple cores |
   Random | Random item recommender for use as experimental baseline |
   SLIM | Abstract class for SLIM based item predictors proposed by Ning and Karypis |
   SoftMarginRankingMF | Matrix factorization model for item prediction optimized for a soft margin (hinge) ranking loss, using stochastic gradient descent (as in BPR-MF). |
   UserAttributeKNN | k-nearest neighbor (kNN) user-based collaborative filtering using the correlation of the user attibutes |
   UserKNN | k-nearest neighbor user-based collaborative filtering |
   WeightedBPRMF | Weigthed BPR-MF with frequency-adjusted sampling |
   WRMF | Weighted matrix factorization method proposed by Hu et al. and Pan et al. |
   Zero | Constant item recommender for use as experimental baseline. Always predicts a score of zero |
  RatingPrediction | This namespace contains rating predictors and some helper classes for rating prediction |
   BiasedMatrixFactorization | Matrix factorization with explicit user and item bias, learning is performed by stochastic gradient descent |
   BiPolarSlopeOne | Bi-polar frequency-weighted Slope-One rating prediction |
   CoClustering | Co-clustering for rating prediction |
   Constant | Uses a constant rating value for prediction |
   EntityAverage | Abstract class that uses an average (by entity) rating value for predictions |
   Extensions | Class that contains static methods for rating prediction |
   ExternalRatingPredictor | Uses externally computed predictions |
   FactorWiseMatrixFactorization | Matrix factorization with factor-wise learning |
   FoldInRatingPredictorExtensions | Extension methods for IFoldInRatingPredictor |
   GlobalAverage | Uses the average rating value over all ratings for prediction |
   GSVDPlusPlus | Item Attribute Aware SVD++: Matrix factorization that also takes into account what users have rated and its attributes. |
   IFoldInRatingPredictor | Rating predictor that allows folding in new users |
   IIncrementalRatingPredictor | Interface for rating predictors which support incremental training |
   IncrementalRatingPredictor | Base class for rating predictors that support incremental training |
   IRatingPredictor | Interface for rating predictors |
   ItemAttributeKNN | Attribute-aware weighted item-based kNN recommender |
   ItemAverage | Uses the average rating value of an item for prediction |
   ItemKNN | Weighted item-based kNN |
   ITimeAwareRatingPredictor | Interface for time-aware rating predictors |
   ITransductiveRatingPredictor | Rating predictor that knows beforehand what it will have to rate |
   KNN | Base class for rating predictors that use some kind of kNN |
   LatentFeatureLogLinearModel | Latent-feature log linear model |
   MatrixFactorization | Simple matrix factorization class, learning is performed by stochastic gradient descent (SGD) |
   NaiveBayes | Attribute-aware rating predictor using Naive Bayes |
   Random | Uses a random rating value for prediction |
   RatingPredictor | Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction) |
   SigmoidCombinedAsymmetricFactorModel | Asymmetric factor model which represents items in terms of the users that rated them, and users in terms of the items they rated |
   SigmoidItemAsymmetricFactorModel | Asymmetric factor model |
   SigmoidSVDPlusPlus | SVD++: Matrix factorization that also takes into account what users have rated; variant that uses a sigmoid function |
   SigmoidUserAsymmetricFactorModel | Asymmetric factor model which represents items in terms of the users that rated them |
   SlopeOne | Frequency-weighted Slope-One rating prediction |
   SocialMF | Social-network-aware matrix factorization |
   SVDPlusPlus | SVD++: Matrix factorization that also takes into account what users have rated |
   TimeAwareBaseline | Time-aware bias model |
   TimeAwareBaselineWithFrequencies | Time-aware bias model with frequencies |
   TimeAwareRatingPredictor | Abstract class for time-aware rating predictors |
   TransductiveRatingPredictorExtensions | Helper methods for ITransductiveRatingPredictor |
   UserAttributeKNN | Weighted kNN recommender based on user attributes |
   UserAverage | Uses the average rating value of a user for predictions |
   UserItemBaseline | Baseline method for rating prediction |
   UserKNN | Weighted user-based kNN |
  Taxonomy | This namespace contains taxonomical data structures, i.e. data structures that help us to describe what kind of a thing something is |
  Extensions | Helper class with utility methods for handling recommenders |
  Handlers | Class containing handler functions, e.g. exception handlers |
  IIncrementalRecommender | Interface for recommenders that support incremental model updates. |
  IItemAttributeAwareRecommender | Interface for recommenders that take binary item attributes into account |
  IItemRelationAwareRecommender | Interface for recommenders that take a binary relation over items into account |
  IItemSimilarityProvider | Interface for classes that provide item similarities |
  IIterativeModel | Interface representing iteratively trained models |
  INeedsMappings | Interface for classes that need user and item ID mappings, e.g. for recommenders that read data from external sources and thus need to know which IDs are used externally. |
  IRecommender | Generic interface for simple recommenders |
  IUserAttributeAwareRecommender | Interface for recommenderss that take binary user attributes into account |
  IUserRelationAwareRecommender | Interface for recommenders that take a binary relation over users into account |
  IUserSimilarityProvider | Interface for classes that provide user similarities |
  Memory | Memory-related tools |
  MultiCore | Utility routines for multi-core algorithms |
  Random | Random number generator singleton class |
  Recommender | Abstract recommender class implementing default behaviors |
  RecommenderParameters | Class for key-value pair string processing |
  Utils | Class containing utility functions |
  Wrap | Static methods to wrap around other code. |