net.librec.recommender.cf.ranking

Class ListRankMFRecommender

java.lang.Object

net.librec.recommender.AbstractRecommender

net.librec.recommender.MatrixFactorizationRecommender

net.librec.recommender.cf.ranking.ListRankMFRecommender

All Implemented Interfaces:

Recommender

public class ListRankMFRecommender
extends MatrixFactorizationRecommender

Shi et al., List-wise learning to rank with matrix factorization for collaborative filtering, RecSys 2010. Alpha version

Author:

Yuanyuan Jin and Keqiang Wang

Field Summary

Fields

Modifier and Type	Field and Description
DenseVector	userExp

Fields inherited from class net.librec.recommender.MatrixFactorizationRecommender

initMean, initStd, itemFactors, learnRate, maxLearnRate, numFactors, numIterations, regItem, regUser, userFactors

Fields inherited from class net.librec.recommender.AbstractRecommender

conf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, lastLoss, LOG, loss, maxRate, minRate, numItems, numRates, numUsers, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose

Constructor Summary

Constructors

Constructor and Description
ListRankMFRecommender()

Method Summary

Methods

Modifier and Type	Method and Description
double	getLoss(DenseMatrix userFactors, DenseMatrix itemFactors)
protected void	setup() setup init member method
protected void	trainModel() train Model

Methods inherited from class net.librec.recommender.MatrixFactorizationRecommender

predict, updateLRate

Methods inherited from class net.librec.recommender.AbstractRecommender

cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext

Methods inherited from class java.lang.Object

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

Field Detail

userExp

public DenseVector userExp

Constructor Detail

ListRankMFRecommender

public ListRankMFRecommender()

Method Detail

setup

protected void setup()
              throws LibrecException

Description copied from class: MatrixFactorizationRecommender

setup init member method

Overrides:

setup in class MatrixFactorizationRecommender

Throws:

LibrecException - if error occurs during setting up

trainModel

protected void trainModel()
                   throws LibrecException

Description copied from class: AbstractRecommender

train Model

Specified by:

trainModel in class AbstractRecommender

Throws:

LibrecException - if error occurs during training model

getLoss

public double getLoss(DenseMatrix userFactors,
             DenseMatrix itemFactors)