CAttributeData | Class that offers static methods to read (binary) attribute data into IBooleanMatrix objects |
CAUC | Area under the ROC curve (AUC) of a list of ranked items |
CConstants | Static class containing constants used by the MyMediaLite Input/Output routines |
CDataReaderExtensions | Extension methods for IDataReader objects |
►CDictionary | |
►CEvaluationResults | Class for representing evaluation results |
CItemRecommendationEvaluationResults | Item recommendation evaluation results |
CRatingPredictionEvaluationResults | Rating prediction evaluation results |
CRecommenderParameters | Class for key-value pair string processing |
CEntityMappingExtensions | I/O routines for classes implementing the IEntityMapping interface |
CExtensions | Extension methods for correlation matrices |
CExtensions | Class that contains static methods for rating prediction |
CExtensions | Extension methods for dataset statistics |
CExtensions | Helper class with utility methods for handling recommenders |
CExtensions | Class that contains static methods for item prediction |
CFileSerializer | Static class for serializing objects to binary files |
CFileSystem | File-system related helper functions |
CFoldIn | Fold-in evaluation |
CFoldInRatingPredictorExtensions | Extension methods for IFoldInRatingPredictor |
CGridSearch | Grid search for finding suitable hyperparameters |
CHandlers | Class containing handler functions, e.g. exception handlers |
►CICloneable | |
►CIRecommender | Generic interface for simple recommenders |
►CEnsemble | Abtract class for combining several prediction methods |
CWeightedEnsemble | Combining several predictors with a weighted ensemble |
►CIItemAttributeAwareRecommender | Interface for recommenders that take binary item attributes into account |
CItemAttributeKNN | k-nearest neighbor (kNN) item-based collaborative filtering using the correlation of the item attibutes |
CMostPopularByAttributes | Recommend most popular items by attribute |
CGSVDPlusPlus | Item Attribute Aware SVD++: Matrix factorization that also takes into account what users have rated and its attributes. |
CItemAttributeKNN | Attribute-aware weighted item-based kNN recommender |
CNaiveBayes | Attribute-aware rating predictor using Naive Bayes |
CIItemRelationAwareRecommender | Interface for recommenders that take a binary relation over items into account |
►CIFoldInItemRecommender | Item recommender that allows folding in new users |
►CBPRMF | Matrix factorization model for item prediction (ranking) optimized for BPR |
CMultiCoreBPRMF | Matrix factorization for BPR on multiple cores |
CSoftMarginRankingMF | Matrix factorization model for item prediction optimized for a soft margin (hinge) ranking loss, using stochastic gradient descent (as in BPR-MF). |
CWeightedBPRMF | Weigthed BPR-MF with frequency-adjusted sampling |
►CUserKNN | k-nearest neighbor user-based collaborative filtering |
CUserAttributeKNN | k-nearest neighbor (kNN) user-based collaborative filtering using the correlation of the user attibutes |
►CIUserAttributeAwareRecommender | Interface for recommenderss that take binary user attributes into account |
CUserAttributeKNN | k-nearest neighbor (kNN) user-based collaborative filtering using the correlation of the user attibutes |
CUserAttributeKNN | Weighted kNN recommender based on user attributes |
►CIUserRelationAwareRecommender | Interface for recommenders that take a binary relation over users into account |
CSocialMF | Social-network-aware matrix factorization |
►CIRatingPredictor | Interface for rating predictors |
►CIFoldInRatingPredictor | Rating predictor that allows folding in new users |
►CItemKNN | Weighted item-based kNN |
CItemAttributeKNN | Attribute-aware weighted item-based kNN recommender |
►CMatrixFactorization | Simple matrix factorization class, learning is performed by stochastic gradient descent (SGD) |
►CBiasedMatrixFactorization | Matrix factorization with explicit user and item bias, learning is performed by stochastic gradient descent |
CSigmoidCombinedAsymmetricFactorModel | Asymmetric factor model which represents items in terms of the users that rated them, and users in terms of the items they rated |
CSigmoidItemAsymmetricFactorModel | Asymmetric factor model |
CSigmoidUserAsymmetricFactorModel | Asymmetric factor model which represents items in terms of the users that rated them |
CSocialMF | Social-network-aware matrix factorization |
►CSVDPlusPlus | SVD++: Matrix factorization that also takes into account what users have rated |
CGSVDPlusPlus | Item Attribute Aware SVD++: Matrix factorization that also takes into account what users have rated and its attributes. |
CSigmoidSVDPlusPlus | SVD++: Matrix factorization that also takes into account what users have rated; variant that uses a sigmoid function |
CUserAverage | Uses the average rating value of a user for predictions |
►CUserKNN | Weighted user-based kNN |
CUserAttributeKNN | Weighted kNN recommender based on user attributes |
►CIIncrementalRatingPredictor | Interface for rating predictors which support incremental training |
►CIncrementalRatingPredictor | Base class for rating predictors that support incremental training |
CConstant | Uses a constant rating value for prediction |
►CEntityAverage | Abstract class that uses an average (by entity) rating value for predictions |
CItemAverage | Uses the average rating value of an item for prediction |
CUserAverage | Uses the average rating value of a user for predictions |
CGlobalAverage | Uses the average rating value over all ratings for prediction |
►CKNN | Base class for rating predictors that use some kind of kNN |
CItemKNN | Weighted item-based kNN |
CUserKNN | Weighted user-based kNN |
CMatrixFactorization | Simple matrix factorization class, learning is performed by stochastic gradient descent (SGD) |
CNaiveBayes | Attribute-aware rating predictor using Naive Bayes |
CRandom | Uses a random rating value for prediction |
CUserItemBaseline | Baseline method for rating prediction |
►CITimeAwareRatingPredictor | Interface for time-aware rating predictors |
►CTimeAwareRatingPredictor | Abstract class for time-aware rating predictors |
►CTimeAwareBaseline | Time-aware bias model |
CTimeAwareBaselineWithFrequencies | Time-aware bias model with frequencies |
►CITransductiveRatingPredictor | Rating predictor that knows beforehand what it will have to rate |
CSigmoidCombinedAsymmetricFactorModel | Asymmetric factor model which represents items in terms of the users that rated them, and users in terms of the items they rated |
CSigmoidItemAsymmetricFactorModel | Asymmetric factor model |
CSigmoidSVDPlusPlus | SVD++: Matrix factorization that also takes into account what users have rated; variant that uses a sigmoid function |
CSigmoidUserAsymmetricFactorModel | Asymmetric factor model which represents items in terms of the users that rated them |
CSVDPlusPlus | SVD++: Matrix factorization that also takes into account what users have rated |
►CRatingPredictor | Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction) |
CBiPolarSlopeOne | Bi-polar frequency-weighted Slope-One rating prediction |
CCoClustering | Co-clustering for rating prediction |
CExternalRatingPredictor | Uses externally computed predictions |
CFactorWiseMatrixFactorization | Matrix factorization with factor-wise learning |
CIncrementalRatingPredictor | Base class for rating predictors that support incremental training |
CLatentFeatureLogLinearModel | Latent-feature log linear model |
CSlopeOne | Frequency-weighted Slope-One rating prediction |
CTimeAwareRatingPredictor | Abstract class for time-aware rating predictors |
►CRecommender | Abstract recommender class implementing default behaviors |
►CItemRecommender | Abstract item recommender class that loads the (positive-only implicit feedback) training data into memory and provides flexible access to it. |
CExternalItemRecommender | Uses externally computed predictions |
►CIncrementalItemRecommender | Base class for item recommenders that support incremental updates |
►CKNN | Base class for item recommenders that use some kind of k-nearest neighbors (kNN) model |
►CItemKNN | k-nearest neighbor (kNN) item-based collaborative filtering |
CItemAttributeKNN | k-nearest neighbor (kNN) item-based collaborative filtering using the correlation of the item attibutes |
CUserKNN | k-nearest neighbor user-based collaborative filtering |
►CMF | Abstract class for matrix factorization based item predictors |
CBPRMF | Matrix factorization model for item prediction (ranking) optimized for BPR |
CWRMF | Weighted matrix factorization method proposed by Hu et al. and Pan et al. |
CMostPopular | Most-popular item recommender |
►CSLIM | Abstract class for SLIM based item predictors proposed by Ning and Karypis |
CBPRSLIM | Sparse Linear Methods (SLIM) for item prediction (ranking) optimized for BPR-Opt optimization criterion |
CLeastSquareSLIM | Sparse Linear Methods (SLIM) for item prediction (ranking) optimized for the elastic net loss |
CMostPopularByAttributes | Recommend most popular items by attribute |
CRandom | Random item recommender for use as experimental baseline |
CZero | Constant item recommender for use as experimental baseline. Always predicts a score of zero |
CRatingPredictor | Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction) |
►CIDataSet | Interface for different kinds of collaborative filtering data sets |
►CDataSet | Abstract dataset class that implements some common functions |
CPosOnlyFeedback< T > | Data structure for implicit, positive-only user feedback |
►CRatings | Data structure for storing ratings |
CCombinedRatings | Combine two IRatings objects |
CRatingsProxy | Data structure that allows access to selected entries of a rating data structure |
►CStaticRatings | Array-based storage for rating data. |
CStaticByteRatings | Array-based storage for rating data. |
►CTimedRatings | Data structure for storing ratings with time information |
CTimedRatingsProxy | Data structure that allows access to selected entries of a timed rating data structure |
►CIPosOnlyFeedback | Interface for implicit, positive-only user feedback |
CPosOnlyFeedback< T > | Data structure for implicit, positive-only user feedback |
►CIRatings | Interface for rating datasets |
►CITimedRatings | Interface for rating datasets with time information |
CTimedRatings | Data structure for storing ratings with time information |
CRatings | Data structure for storing ratings |
►CITimedDataSet | interface for data sets with time information |
CITimedRatings | Interface for rating datasets with time information |
CIHyperParameterSearch | Interface for classes that perform hyper-parameter search |
►CIIncrementalRecommender | Interface for recommenders that support incremental model updates. |
►CIIncrementalItemRecommender | Interface for item recommenders |
CIncrementalItemRecommender | Base class for item recommenders that support incremental updates |
CIIncrementalRatingPredictor | Interface for rating predictors which support incremental training |
►CIItemSimilarityProvider | Interface for classes that provide item similarities |
CItemKNN | k-nearest neighbor (kNN) item-based collaborative filtering |
CItemKNN | Weighted item-based kNN |
►CIIterativeModel | Interface representing iteratively trained models |
CMF | Abstract class for matrix factorization based item predictors |
CSLIM | Abstract class for SLIM based item predictors proposed by Ning and Karypis |
CCoClustering | Co-clustering for rating prediction |
CFactorWiseMatrixFactorization | Matrix factorization with factor-wise learning |
CLatentFeatureLogLinearModel | Latent-feature log linear model |
CMatrixFactorization | Simple matrix factorization class, learning is performed by stochastic gradient descent (SGD) |
CTimeAwareBaseline | Time-aware bias model |
CUserItemBaseline | Baseline method for rating prediction |
►CIList | |
CIRatings | Interface for rating datasets |
CCombinedList< T > | Combines two List objects |
CListProxy< T > | Proxy class that allows access to selected elements of an underlying list data structure |
►CIMapping | Interface to map external entity IDs to internal ones to ensure that there are no gaps in the numbering |
CIdentityMapping | Identity mapping for entity IDs: Every original ID is mapped to itself |
CMapping | Class to map external entity IDs to internal ones to ensure that there are no gaps in the numbering |
►CIMatrix< T > | Generic interface for matrix data types |
CMatrix< T > | Class for storing dense matrices |
►CSparseMatrix< T > | Class for storing sparse matrices |
CSymmetricSparseMatrix< T > | a symmetric sparse matrix; consumes less memory |
CSymmetricMatrix< T > | Class for storing dense matrices |
►CIMatrix< bool > | |
►CIBooleanMatrix | Interface for boolean matrices |
CSparseBooleanMatrix | Sparse representation of a boolean matrix, using HashSets |
►CIMatrix< float > | |
►CICorrelationMatrix | Interface representing correlation and similarity matrices |
►CAsymmetricCorrelationMatrix | Class for computing and storing correlations and similarities |
►CBinaryDataAsymmetricCorrelationMatrix | Class with commoin routines for asymmetric correlations that are learned from binary data |
CBidirectionalConditionalProbability | Class for storing and computing 'bi-directional' conditional probabilities |
CConditionalProbability | Class for storing and computing conditional probabilities |
►CIBinaryDataCorrelationMatrix | CorrelationMatrix that computes correlations over binary data |
CBinaryDataAsymmetricCorrelationMatrix | Class with commoin routines for asymmetric correlations that are learned from binary data |
►CBinaryDataSymmetricCorrelationMatrix | Class with common routines for symmetric correlations that are learned from binary data |
CBinaryCosine | Class for storing cosine similarities |
CCooccurrence | Class for storing and computing the co-counts |
CJaccard | Class for storing and computing the Jaccard index (Tanimoto coefficient) |
►CIRatingCorrelationMatrix | CorrelationMatrix that computes correlations over rating data |
►CPearson | Shrunk Pearson correlation for rating data |
CRatingCosine | Rating cosine similarity for rating data |
►CSymmetricCorrelationMatrix | Class for computing and storing correlations and similarities |
CBinaryDataSymmetricCorrelationMatrix | Class with common routines for symmetric correlations that are learned from binary data |
CPearson | Shrunk Pearson correlation for rating data |
►CINeedsMappings | 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. |
CExternalItemRecommender | Uses externally computed predictions |
CExternalRatingPredictor | Uses externally computed predictions |
►CISerializable | |
CDataSet | Abstract dataset class that implements some common functions |
CMapping | Class to map external entity IDs to internal ones to ensure that there are no gaps in the numbering |
CPosOnlyFeedback< T > | Data structure for implicit, positive-only user feedback |
CISplit< T > | generic dataset splitter interface |
►CISplit< IPosOnlyFeedback > | |
CPosOnlyFeedbackCrossValidationSplit< T > | K-fold cross-validation split for item prediction from implicit feedback |
CPosOnlyFeedbackSimpleSplit< T > | simple split for item prediction from implicit feedback |
►CISplit< IRatings > | |
CRatingCrossValidationSplit | k-fold cross-validation split for rating prediction |
CRatingsSimpleSplit | simple split for rating prediction |
►CISplit< ITimedRatings > | |
CRatingsChronologicalSplit | chronological split for rating prediction |
CRatingsPerUserChronologicalSplit | per-user chronological split for rating prediction |
CItemData | Class that contains static methods for reading in implicit feedback data for ItemRecommender |
CItemDataRatingThreshold | Class that contains static methods for reading in implicit feedback data for ItemRecommender, derived from rating data |
CItems | Evaluation class for item recommendation |
CItems | Routines for reading in the item taxonomy of the KDD Cup 2011 data |
CItemsCrossValidation | Cross-validation for item recommendation |
CItemsOnline | Online evaluation for rankings of items |
CITransductiveItemRecommender | Interface for item recommenders that take into account some test data for training |
►CIUserSimilarityProvider | Interface for classes that provide user similarities |
CUserKNN | k-nearest neighbor user-based collaborative filtering |
CUserKNN | Weighted user-based kNN |
CKDDCupItems | Represents KDD Cup 2011 items like album, track, artist, or genre |
CLogisticLoss | Utility functions for the logistic loss |
CMAE | Utility functions for the mean absolute error |
CMatrix< float > | |
CMatrixExtensions | Utilities to work with matrices |
CMatrixExtensions | Utilities to work with matrices |
CMemory | Memory-related tools |
CModel | Class containing static routines for reading and writing recommender models |
CMovieLensRatingData | Class that offers static methods for reading in MovieLens 1M and 10M rating data |
CMultiCore | Utility routines for multi-core algorithms |
CNDCG | Normalized discounted cumulative gain (NDCG) of a list of ranked items |
CNelderMead | Nealder-Mead algorithm for finding suitable hyperparameters |
COverlap | Class containing routines for computing overlaps |
CPrecisionAndRecall | Precision and recall at different positions in the list |
►CRandom | |
CRandom | Random number generator singleton class |
CRatingBasedRankingCrossValidation | Cross-validation for rating-based ranking |
CRatingData | Class that offers methods for reading in rating data |
CRatings | Evaluation class for rating prediction |
CRatings | Class that offers static methods for reading in rating data from the KDD Cup 2011 files |
CRatingScale | Class containing information about the rating scale of a data set: valid rating values, minimum/maximum rating. |
CRatingsCrossValidation | Cross-validation for rating prediction |
CRatingsOnline | Online evaluation for rating prediction |
CReciprocalRank | The reciprocal rank of a list of ranked items |
CRelationData | Class that offers static methods to read (binary) relation over entities into IBooleanMatrix objects |
CRMSE | Utility functions for the root mean square error (RMSE) |
CSequentialDiversification | Sequential diversification |
►CSparseMatrix< float > | |
CAsymmetricCorrelationMatrix | Class for computing and storing correlations and similarities |
CSparseMatrixExtensions | Utilities to work with matrices |
CStaticRatingData | Class that offers methods for reading in static rating data |
►CSymmetricSparseMatrix< float > | |
CSymmetricCorrelationMatrix | Class for computing and storing correlations and similarities |
CSkewSymmetricSparseMatrix | a skew symmetric (anti-symmetric) sparse matrix; consumes less memory |
CSymmetricSparseMatrix< int > | |
CTimedRatingData | Class that offers methods for reading in rating data with time information |
CTrack2Items | Class that offers static methods for reading in test data from the KDD Cup 2011 files |
CTransductiveRatingPredictorExtensions | Helper methods for ITransductiveRatingPredictor |
CUtils | Class containing utility functions |
CVectorExtensions | Extensions for vector-like data |
CVectorExtensions | Extensions for vector-like data |
CWrap | Static methods to wrap around other code. |