public class LLORMARecommender extends MatrixFactorizationRecommender
This implementation refers to the method proposed by Lee et al. at ICML 2013.
Lcoal Structure: Joonseok Lee, Local Low-Rank Matrix Approximation , ICML. 2013: 82-90.
| Modifier and Type | Field and Description |
|---|---|
protected double |
globalRegItem |
protected double |
globalRegUser |
protected double |
localRegItem |
protected double |
localRegUser |
initMean, initStd, itemFactors, learnRate, maxLearnRate, numFactors, numIterations, regItem, regUser, userFactorsconf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, lastLoss, LOG, loss, maxRate, minRate, numItems, numRates, numUsers, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose| Constructor and Description |
|---|
LLORMARecommender() |
| Modifier and Type | Method and Description |
|---|---|
protected double |
predict(int userIdx,
int itemIdx)
predict a specific rating for user userIdx on item itemIdx.
|
protected void |
setup()
setup
init member method
|
protected void |
trainModel()
train Model
|
updateLRatecleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContextprotected double globalRegUser
protected double globalRegItem
protected double localRegUser
protected double localRegItem
protected void setup()
throws LibrecException
MatrixFactorizationRecommendersetup in class MatrixFactorizationRecommenderLibrecException - if error occurs during setting upprotected void trainModel()
throws LibrecException
AbstractRecommendertrainModel in class AbstractRecommenderLibrecException - if error occurs during training modelprotected double predict(int userIdx,
int itemIdx)
MatrixFactorizationRecommenderpredict in class MatrixFactorizationRecommenderuserIdx - user indexitemIdx - item indexCopyright © 2017. All Rights Reserved.