Package MyMediaLite.RatingPrediction

This namespace contains rating predictors and some helper classes for rating prediction. More...

Classes
class	BiasedMatrixFactorization
	Matrix factorization with explicit user and item bias, learning is performed by stochastic gradient descent More...
class	BiPolarSlopeOne
	Bi-polar frequency-weighted Slope-One rating prediction More...
class	CoClustering
	Co-clustering for rating prediction More...
class	Constant
	Uses a constant rating value for prediction More...
class	EntityAverage
	Abstract class that uses an average (by entity) rating value for predictions More...
class	Extensions
	Class that contains static methods for rating prediction More...
class	ExternalRatingPredictor
	Uses externally computed predictions More...
class	FactorWiseMatrixFactorization
	Matrix factorization with factor-wise learning More...
class	FoldInRatingPredictorExtensions
	Extension methods for IFoldInRatingPredictor More...
class	GlobalAverage
	Uses the average rating value over all ratings for prediction More...
class	GSVDPlusPlus
	Item Attribute Aware SVD++: Matrix factorization that also takes into account what users have rated and its attributes. More...
interface	IFoldInRatingPredictor
	Rating predictor that allows folding in new users More...
interface	IIncrementalRatingPredictor
	Interface for rating predictors which support incremental training More...
class	IncrementalRatingPredictor
	Base class for rating predictors that support incremental training More...
interface	IRatingPredictor
	Interface for rating predictors More...
class	ItemAttributeKNN
	Attribute-aware weighted item-based kNN recommender More...
class	ItemAverage
	Uses the average rating value of an item for prediction More...
class	ItemKNN
	Weighted item-based kNN More...
interface	ITimeAwareRatingPredictor
	Interface for time-aware rating predictors More...
interface	ITransductiveRatingPredictor
	Rating predictor that knows beforehand what it will have to rate More...
class	KNN
	Base class for rating predictors that use some kind of kNN More...
class	LatentFeatureLogLinearModel
	Latent-feature log linear model More...
class	MatrixFactorization
	Simple matrix factorization class, learning is performed by stochastic gradient descent (SGD) More...
class	NaiveBayes
	Attribute-aware rating predictor using Naive Bayes More...
class	Random
	Uses a random rating value for prediction More...
class	RatingPredictor
	Abstract class for rating predictors that keep the rating data in memory for training (and possibly prediction) More...
class	SigmoidCombinedAsymmetricFactorModel
	Asymmetric factor model which represents items in terms of the users that rated them, and users in terms of the items they rated More...
class	SigmoidItemAsymmetricFactorModel
	Asymmetric factor model More...
class	SigmoidSVDPlusPlus
	SVD++: Matrix factorization that also takes into account what users have rated; variant that uses a sigmoid function More...
class	SigmoidUserAsymmetricFactorModel
	Asymmetric factor model which represents items in terms of the users that rated them More...
class	SlopeOne
	Frequency-weighted Slope-One rating prediction More...
class	SocialMF
	Social-network-aware matrix factorization More...
class	SVDPlusPlus
	SVD++: Matrix factorization that also takes into account what users have rated More...
class	TimeAwareBaseline
	Time-aware bias model More...
class	TimeAwareBaselineWithFrequencies
	Time-aware bias model with frequencies More...
class	TimeAwareRatingPredictor
	Abstract class for time-aware rating predictors More...
class	TransductiveRatingPredictorExtensions
	Helper methods for ITransductiveRatingPredictor More...
class	UserAttributeKNN
	Weighted kNN recommender based on user attributes More...
class	UserAverage
	Uses the average rating value of a user for predictions More...
class	UserItemBaseline
	Baseline method for rating prediction More...
class	UserKNN
	Weighted user-based kNN More...

Enumerations
enum	OptimizationTarget { RMSE, MAE, LogisticLoss }
	Enumeration to represent different optimization targets for rating prediction More...

Detailed Description

This namespace contains rating predictors and some helper classes for rating prediction.

Enumeration Type Documentation

enum OptimizationTarget

Enumeration to represent different optimization targets for rating prediction

Enumerator
RMSE	(root) mean square error
MAE	mean absolute error
LogisticLoss	log likelihood of the data (as in logistic regression)