moa.recommender.rc.predictor.impl

Class BRISMFPredictor

java.lang.Object

moa.recommender.rc.predictor.impl.BRISMFPredictor

All Implemented Interfaces:

Updatable

public class BRISMFPredictor
extends Object
implements Updatable

Implementation of the algorithm described in Scalable Collaborative Filtering Approaches for Large Recommender Systems (Gábor Takács, István Pilászy, Bottyán Németh, and Domonkos Tikk). A feature vector is learned for every user and item, so that the prediction of a rating is roughly the dot product of the corresponding user and item vector. Stochastic gradient descent is used to train the model, minimizing its prediction error. Both Tikhonov regularization and early stopping are used to reduce overfitting. The algorithm allows batch training (from scratch, using all ratings available at the moment) as well as incremental, by retraining only the affected user and item vectors when a new rating is inserted.

Parameters:

• features - the number of features to be trained for each user and item
• learning rate - the learning rate used in the regularization
• ratio - the regularization ratio to be used in the Tikhonov regularization
• iterations - the number of iterations to be used when retraining user and item features (online training).

Field Summary

Fields

Modifier and Type	Field and Description
protected RecommenderData	data
protected HashMap<Integer,float[]>	itemFeature
protected double	lRate
protected int	nFeatures
protected int	nIterations
protected double	rFactor
protected Random	rnd
protected HashMap<Integer,float[]>	userFeature

Constructor Summary

Constructors

Constructor and Description
BRISMFPredictor(int nFeatures, RecommenderData data, boolean train)
BRISMFPredictor(int nFeatures, RecommenderData data, double lRate, double rFactor, boolean train)

Method Summary

Methods

Modifier and Type	Method and Description
RecommenderData	getData()
float[]	getItemFeatures(int itemID)
int	getNumFeatures()
float[]	getUserFeatures(int userID)
double	predictRating(float[] userFeats, float[] itemFeats)
double	predictRating(int userID, int itemID)
List<Double>	predictRatings(int userID, List<Integer> itemIDS)
void	setLRate(double lRate)
void	setNIterations(int nIterations)
void	setRFactor(double rFactor)
void	train()
void	trainItem(int itemID)
void	trainItem(int itemID, int nIts)
void	trainItem(int itemID, List<Integer> usr, List<Double> rat)
void	trainItem(int itemID, List<Integer> usr, List<Double> rat, int nIts)
float[]	trainItemFeats(int itemID, List<Integer> usr, List<Double> rat, int nIts)
void	trainUser(int userID)
void	trainUser(int userID, int nIts)
void	trainUser(int userID, List<Integer> itm, List<Double> rat)
void	trainUser(int userID, List<Integer> itm, List<Double> rat, int nIts)
float[]	trainUserFeats(List<Integer> itm, List<Double> rat, int nIts)
void	updateNewItem(int itemID, List<Integer> ratingUsers, List<Double> ratings)
void	updateNewUser(int userID, List<Integer> ratedItems, List<Double> ratings)
void	updateRemoveItem(int itemID)
void	updateRemoveRating(int userID, int itemID)
void	updateRemoveUser(int userID)
void	updateSetRating(int userID, int itemID, double rating)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

data

protected RecommenderData data

nFeatures

protected int nFeatures

userFeature

protected HashMap<Integer,float[]> userFeature

itemFeature

protected HashMap<Integer,float[]> itemFeature

rnd

protected Random rnd

lRate

protected double lRate

rFactor

protected double rFactor

nIterations

protected int nIterations

Constructor Detail

BRISMFPredictor

public BRISMFPredictor(int nFeatures,
               RecommenderData data,
               boolean train)

BRISMFPredictor

public BRISMFPredictor(int nFeatures,
               RecommenderData data,
               double lRate,
               double rFactor,
               boolean train)

Method Detail

setLRate

public void setLRate(double lRate)

setRFactor

public void setRFactor(double rFactor)

setNIterations

public void setNIterations(int nIterations)

getData

public RecommenderData getData()

predictRating

public double predictRating(int userID,
                   int itemID)

predictRating

public double predictRating(float[] userFeats,
                   float[] itemFeats)

trainUserFeats

public float[] trainUserFeats(List<Integer> itm,
                     List<Double> rat,
                     int nIts)

trainItemFeats

public float[] trainItemFeats(int itemID,
                     List<Integer> usr,
                     List<Double> rat,
                     int nIts)

trainUser

public void trainUser(int userID,
             List<Integer> itm,
             List<Double> rat,
             int nIts)

trainUser

public void trainUser(int userID,
             int nIts)

trainUser

public void trainUser(int userID,
             List<Integer> itm,
             List<Double> rat)

trainItem

public void trainItem(int itemID)

trainItem

public void trainItem(int itemID,
             int nIts)

trainUser

public void trainUser(int userID)

trainItem

public void trainItem(int itemID,
             List<Integer> usr,
             List<Double> rat)

trainItem

public void trainItem(int itemID,
             List<Integer> usr,
             List<Double> rat,
             int nIts)

train

public void train()

getUserFeatures

public float[] getUserFeatures(int userID)

getItemFeatures

public float[] getItemFeatures(int itemID)

getNumFeatures

public int getNumFeatures()

updateNewUser

public void updateNewUser(int userID,
                 List<Integer> ratedItems,
                 List<Double> ratings)

Specified by:

updateNewUser in interface Updatable

updateNewItem

public void updateNewItem(int itemID,
                 List<Integer> ratingUsers,
                 List<Double> ratings)

Specified by:

updateNewItem in interface Updatable

updateRemoveUser

public void updateRemoveUser(int userID)

Specified by:

updateRemoveUser in interface Updatable

updateRemoveItem

public void updateRemoveItem(int itemID)

Specified by:

updateRemoveItem in interface Updatable

updateSetRating

public void updateSetRating(int userID,
                   int itemID,
                   double rating)

Specified by:

updateSetRating in interface Updatable

updateRemoveRating

public void updateRemoveRating(int userID,
                      int itemID)

Specified by:

updateRemoveRating in interface Updatable

predictRatings

public List<Double> predictRatings(int userID,
                          List<Integer> itemIDS)