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

Packages that use DataModel

Package	Description
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

Modifier and Type	Method and Description
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

Modifier and Type	Method and Description
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

Modifier and Type	Method and Description
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

Modifier and Type	Class and Description
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

Modifier and Type	Method and Description
protected DataModel	PlusAnonymousUserDataModel.getDelegate()

Methods in org.apache.mahout.cf.taste.impl.model with parameters of type DataModel

Modifier and Type	Method and Description
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

Constructor and Description
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

Modifier and Type	Class and Description
class	FileDataModel A DataModel backed by a delimited file.

Methods in org.apache.mahout.cf.taste.impl.model.file that return DataModel

Modifier and Type	Method and Description
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

Constructor and Description
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

Modifier and Type	Method and Description
DataModel	CachingRecommender.getDataModel()
DataModel	AbstractRecommender.getDataModel()

Methods in org.apache.mahout.cf.taste.impl.recommender with parameters of type DataModel

Modifier and Type	Method and Description
protected FastIDSet	AbstractCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel)
protected FastIDSet	SamplingCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel, boolean includeKnownItems)
protected FastIDSet	PreferredItemsNeighborhoodCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel, boolean includeKnownItems) 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, boolean includeKnownItems) return all items the user has not yet seen
protected FastIDSet	AllSimilarItemsCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel, boolean includeKnownItems)
protected abstract FastIDSet	AbstractCandidateItemsStrategy.doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel, boolean includeKnownItems)
FastIDSet	AbstractCandidateItemsStrategy.getCandidateItems(long[] itemIDs, DataModel dataModel)
FastIDSet	AbstractCandidateItemsStrategy.getCandidateItems(long userID, PreferenceArray preferencesFromUser, DataModel dataModel, boolean includeKnownItems)

Constructors in org.apache.mahout.cf.taste.impl.recommender with parameters of type DataModel

Constructor and Description
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

Modifier and Type	Field and Description
protected DataModel	RatingSGDFactorizer.dataModel

Constructors in org.apache.mahout.cf.taste.impl.recommender.svd with parameters of type DataModel

Constructor and Description
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

Modifier and Type	Method and Description
protected DataModel	AbstractItemSimilarity.getDataModel()

Constructors in org.apache.mahout.cf.taste.impl.similarity with parameters of type DataModel

Constructor and Description
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 ItemSimilarity 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

Modifier and Type	Interface and Description
interface	JDBCDataModel

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

Methods in org.apache.mahout.cf.taste.recommender that return DataModel

Modifier and Type	Method and Description
DataModel	Recommender.getDataModel()

Methods in org.apache.mahout.cf.taste.recommender with parameters of type DataModel

Modifier and Type	Method and Description
FastIDSet	MostSimilarItemsCandidateItemsStrategy.getCandidateItems(long[] itemIDs, DataModel dataModel)
FastIDSet	CandidateItemsStrategy.getCandidateItems(long userID, PreferenceArray preferencesFromUser, DataModel dataModel, boolean includeKnownItems)