Uses of Interface
org.apache.mahout.cf.taste.model.DataModel

Packages that use DataModel
org.apache.mahout.cf.taste.eval   
org.apache.mahout.cf.taste.impl.eval   
org.apache.mahout.cf.taste.impl.model   
org.apache.mahout.cf.taste.impl.model.file   
org.apache.mahout.cf.taste.impl.neighborhood   
org.apache.mahout.cf.taste.impl.recommender   
org.apache.mahout.cf.taste.impl.recommender.svd   
org.apache.mahout.cf.taste.impl.similarity   
org.apache.mahout.cf.taste.model   
org.apache.mahout.cf.taste.recommender   
 

Uses of DataModel in org.apache.mahout.cf.taste.eval
 

Methods in org.apache.mahout.cf.taste.eval that return DataModel
 DataModel DataModelBuilder.buildDataModel(FastByIDMap<PreferenceArray> trainingData)
           Builds a DataModel implementation to be used in an evaluation, given training data.
 

Methods in org.apache.mahout.cf.taste.eval with parameters of type DataModel
 Recommender RecommenderBuilder.buildRecommender(DataModel dataModel)
           Builds a Recommender implementation to be evaluated, using the given DataModel.
 double RecommenderEvaluator.evaluate(RecommenderBuilder recommenderBuilder, DataModelBuilder dataModelBuilder, DataModel dataModel, double trainingPercentage, double evaluationPercentage)
           Evaluates the quality of a Recommender's recommendations.
 IRStatistics RecommenderIRStatsEvaluator.evaluate(RecommenderBuilder recommenderBuilder, DataModelBuilder dataModelBuilder, DataModel dataModel, IDRescorer rescorer, int at, double relevanceThreshold, double evaluationPercentage)
           
 FastIDSet RelevantItemsDataSplitter.getRelevantItemsIDs(long userID, int at, double relevanceThreshold, DataModel dataModel)
          During testing, relevant items are removed from a particular users' preferences, and a model is build using this user's other preferences and all other users.
 void RelevantItemsDataSplitter.processOtherUser(long userID, FastIDSet relevantItemIDs, FastByIDMap<PreferenceArray> trainingUsers, long otherUserID, DataModel dataModel)
          Adds a single user and all their preferences to the training model.
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.eval
 

Methods in org.apache.mahout.cf.taste.impl.eval with parameters of type DataModel
static void OrderBasedRecommenderEvaluator.evaluate(DataModel model1, DataModel model2, int samples, RunningAverage tracker, String tag)
           
 double AbstractDifferenceRecommenderEvaluator.evaluate(RecommenderBuilder recommenderBuilder, DataModelBuilder dataModelBuilder, DataModel dataModel, double trainingPercentage, double evaluationPercentage)
           
 IRStatistics GenericRecommenderIRStatsEvaluator.evaluate(RecommenderBuilder recommenderBuilder, DataModelBuilder dataModelBuilder, DataModel dataModel, IDRescorer rescorer, int at, double relevanceThreshold, double evaluationPercentage)
           
static void OrderBasedRecommenderEvaluator.evaluate(Recommender recommender, DataModel model, int samples, RunningAverage tracker, String tag)
           
 FastIDSet GenericRelevantItemsDataSplitter.getRelevantItemsIDs(long userID, int at, double relevanceThreshold, DataModel dataModel)
           
 void GenericRelevantItemsDataSplitter.processOtherUser(long userID, FastIDSet relevantItemIDs, FastByIDMap<PreferenceArray> trainingUsers, long otherUserID, DataModel dataModel)
           
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.model
 

Classes in org.apache.mahout.cf.taste.impl.model that implement DataModel
 class AbstractDataModel
          Contains some features common to all implementations.
 class GenericBooleanPrefDataModel
           A simple DataModel which uses given user data as its data source.
 class GenericDataModel
           A simple DataModel which uses a given List of users as its data source.
 class PlusAnonymousConcurrentUserDataModel
           This is a special thread-safe version of PlusAnonymousUserDataModel which allow multiple concurrent anonymous requests.
 class PlusAnonymousUserDataModel
           This DataModel decorator class is useful in a situation where you wish to recommend to a user that doesn't really exist yet in your actual DataModel.
 

Methods in org.apache.mahout.cf.taste.impl.model that return DataModel
protected  DataModel PlusAnonymousUserDataModel.getDelegate()
           
 

Methods in org.apache.mahout.cf.taste.impl.model with parameters of type DataModel
static FastByIDMap<PreferenceArray> GenericDataModel.toDataMap(DataModel dataModel)
          Exports the simple user IDs and preferences in the data model.
static FastByIDMap<FastIDSet> GenericBooleanPrefDataModel.toDataMap(DataModel dataModel)
          Exports the simple user IDs and associated item IDs in the data model.
 

Constructors in org.apache.mahout.cf.taste.impl.model with parameters of type DataModel
GenericBooleanPrefDataModel(DataModel dataModel)
          Deprecated. without direct replacement. Consider GenericBooleanPrefDataModel.toDataMap(DataModel) with GenericBooleanPrefDataModel.GenericBooleanPrefDataModel(FastByIDMap)
GenericDataModel(DataModel dataModel)
          Deprecated. without direct replacement. Consider GenericDataModel.toDataMap(DataModel) with GenericDataModel.GenericDataModel(FastByIDMap)
PlusAnonymousConcurrentUserDataModel(DataModel delegate, int maxConcurrentUsers)
           
PlusAnonymousUserDataModel(DataModel delegate)
           
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.model.file
 

Classes in org.apache.mahout.cf.taste.impl.model.file that implement DataModel
 class FileDataModel
           A DataModel backed by a delimited file.
 

Methods in org.apache.mahout.cf.taste.impl.model.file that return DataModel
protected  DataModel FileDataModel.buildModel()
           
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.neighborhood
 

Constructors in org.apache.mahout.cf.taste.impl.neighborhood with parameters of type DataModel
CachingUserNeighborhood(UserNeighborhood neighborhood, DataModel dataModel)
           
NearestNUserNeighborhood(int n, double minSimilarity, UserSimilarity userSimilarity, DataModel dataModel)
           
NearestNUserNeighborhood(int n, double minSimilarity, UserSimilarity userSimilarity, DataModel dataModel, double samplingRate)
           
NearestNUserNeighborhood(int n, UserSimilarity userSimilarity, DataModel dataModel)
           
ThresholdUserNeighborhood(double threshold, UserSimilarity userSimilarity, DataModel dataModel)
           
ThresholdUserNeighborhood(double threshold, UserSimilarity userSimilarity, DataModel dataModel, double samplingRate)
           
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.recommender
 

Methods in org.apache.mahout.cf.taste.impl.recommender that return DataModel
 DataModel CachingRecommender.getDataModel()
           
 DataModel AbstractRecommender.getDataModel()
           
 

Methods in org.apache.mahout.cf.taste.impl.recommender with parameters of type DataModel
protected  FastIDSet SamplingCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel)
           
protected  FastIDSet PreferredItemsNeighborhoodCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel)
          returns all items that have not been rated by the user and that were preferred by another user that has preferred at least one item that the current user has preferred too
protected  FastIDSet AllUnknownItemsCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel)
          return all items the user has not yet seen
protected  FastIDSet AllSimilarItemsCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel)
           
protected abstract  FastIDSet AbstractCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel)
           
 FastIDSet AbstractCandidateItemsStrategy.getCandidateItems(long[] itemIDs, DataModel dataModel)
           
 FastIDSet AbstractCandidateItemsStrategy.getCandidateItems(long userID, PreferenceArray preferencesFromUser, DataModel dataModel)
           
 

Constructors in org.apache.mahout.cf.taste.impl.recommender with parameters of type DataModel
AbstractRecommender(DataModel dataModel)
           
AbstractRecommender(DataModel dataModel, CandidateItemsStrategy candidateItemsStrategy)
           
EstimatedPreferenceCapper(DataModel model)
           
GenericBooleanPrefItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity)
           
GenericBooleanPrefItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity, CandidateItemsStrategy candidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy mostSimilarItemsCandidateItemsStrategy)
           
GenericBooleanPrefUserBasedRecommender(DataModel dataModel, UserNeighborhood neighborhood, UserSimilarity similarity)
           
GenericItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity)
           
GenericItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity, CandidateItemsStrategy candidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy mostSimilarItemsCandidateItemsStrategy)
           
GenericUserBasedRecommender(DataModel dataModel, UserNeighborhood neighborhood, UserSimilarity similarity)
           
ItemAverageRecommender(DataModel dataModel)
           
ItemUserAverageRecommender(DataModel dataModel)
           
RandomRecommender(DataModel dataModel)
           
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.recommender.svd
 

Fields in org.apache.mahout.cf.taste.impl.recommender.svd declared as DataModel
protected  DataModel RatingSGDFactorizer.dataModel
           
 

Constructors in org.apache.mahout.cf.taste.impl.recommender.svd with parameters of type DataModel
AbstractFactorizer(DataModel dataModel)
           
ALSWRFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations)
           
ALSWRFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations, boolean usesImplicitFeedback, double alpha)
           
ALSWRFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations, boolean usesImplicitFeedback, double alpha, int numTrainingThreads)
           
ParallelSGDFactorizer.PreferenceShuffler(DataModel dataModel)
           
ParallelSGDFactorizer(DataModel dataModel, int numFeatures, double lambda, int numEpochs)
           
ParallelSGDFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations, double mu0, double decayFactor, int stepOffset, double forgettingExponent)
           
ParallelSGDFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations, double mu0, double decayFactor, int stepOffset, double forgettingExponent, double biasMuRatio, double biasLambdaRatio)
           
ParallelSGDFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations, double mu0, double decayFactor, int stepOffset, double forgettingExponent, double biasMuRatio, double biasLambdaRatio, int numThreads)
           
ParallelSGDFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations, double mu0, double decayFactor, int stepOffset, double forgettingExponent, int numThreads)
           
RatingSGDFactorizer(DataModel dataModel, int numFeatures, double learningRate, double preventOverfitting, double randomNoise, int numIterations, double learningRateDecay)
           
RatingSGDFactorizer(DataModel dataModel, int numFeatures, int numIterations)
           
SVDPlusPlusFactorizer(DataModel dataModel, int numFeatures, double learningRate, double preventOverfitting, double randomNoise, int numIterations, double learningRateDecay)
           
SVDPlusPlusFactorizer(DataModel dataModel, int numFeatures, int numIterations)
           
SVDRecommender(DataModel dataModel, Factorizer factorizer)
           
SVDRecommender(DataModel dataModel, Factorizer factorizer, CandidateItemsStrategy candidateItemsStrategy)
           
SVDRecommender(DataModel dataModel, Factorizer factorizer, CandidateItemsStrategy candidateItemsStrategy, PersistenceStrategy persistenceStrategy)
          Create an SVDRecommender using a persistent store to cache factorizations.
SVDRecommender(DataModel dataModel, Factorizer factorizer, PersistenceStrategy persistenceStrategy)
          Create an SVDRecommender using a persistent store to cache factorizations.
 

Uses of DataModel in org.apache.mahout.cf.taste.impl.similarity
 

Methods in org.apache.mahout.cf.taste.impl.similarity that return DataModel
protected  DataModel AbstractItemSimilarity.getDataModel()
           
 

Constructors in org.apache.mahout.cf.taste.impl.similarity with parameters of type DataModel
AbstractItemSimilarity(DataModel dataModel)
           
AveragingPreferenceInferrer(DataModel dataModel)
           
CachingItemSimilarity(ItemSimilarity similarity, DataModel dataModel)
          Creates this on top of the given ItemSimilarity.
CachingUserSimilarity(UserSimilarity similarity, DataModel dataModel)
          Creates this on top of the given UserSimilarity.
CityBlockSimilarity(DataModel dataModel)
           
EuclideanDistanceSimilarity(DataModel dataModel)
           
EuclideanDistanceSimilarity(DataModel dataModel, Weighting weighting)
           
GenericItemSimilarity(ItemSimilarity otherSimilarity, DataModel dataModel)
           Builds a list of item-item similarities given an GenericItemSimilarity.ItemItemSimilarity implementation and a DataModel, rather than a list of GenericItemSimilarity.ItemItemSimilaritys.
GenericItemSimilarity(ItemSimilarity otherSimilarity, DataModel dataModel, int maxToKeep)
           Like GenericItemSimilarity.GenericItemSimilarity(ItemSimilarity, DataModel) )}, but will only keep the specified number of similarities from the given DataModel.
GenericUserSimilarity(UserSimilarity otherSimilarity, DataModel dataModel)
           
GenericUserSimilarity(UserSimilarity otherSimilarity, DataModel dataModel, int maxToKeep)
           
LogLikelihoodSimilarity(DataModel dataModel)
           
PearsonCorrelationSimilarity(DataModel dataModel)
           
PearsonCorrelationSimilarity(DataModel dataModel, Weighting weighting)
           
SpearmanCorrelationSimilarity(DataModel dataModel)
           
TanimotoCoefficientSimilarity(DataModel dataModel)
           
UncenteredCosineSimilarity(DataModel dataModel)
           
UncenteredCosineSimilarity(DataModel dataModel, Weighting weighting)
           
 

Uses of DataModel in org.apache.mahout.cf.taste.model
 

Subinterfaces of DataModel in org.apache.mahout.cf.taste.model
 interface JDBCDataModel
           
 

Uses of DataModel in org.apache.mahout.cf.taste.recommender
 

Methods in org.apache.mahout.cf.taste.recommender that return DataModel
 DataModel Recommender.getDataModel()
           
 

Methods in org.apache.mahout.cf.taste.recommender with parameters of type DataModel
 FastIDSet MostSimilarItemsCandidateItemsStrategy.getCandidateItems(long[] itemIDs, DataModel dataModel)
           
 FastIDSet CandidateItemsStrategy.getCandidateItems(long userID, PreferenceArray preferencesFromUser, DataModel dataModel)
           
 



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