public class GPLSARecommender extends ProbabilisticGraphicalRecommender
Tempered EM: Thomas Hofmann, Unsupervised Learning by Probabilistic Latent Semantic Analysis, Machine Learning, 42, 177�C196, 2001.
Modifier and Type | Field and Description |
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protected float |
b |
protected int |
numTopics |
protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,java.util.Map<java.lang.Integer,java.lang.Double>> |
Q |
protected static double |
smallValue |
protected float |
smoothWeight |
protected DenseMatrix |
topicItemMu |
protected DenseMatrix |
topicItemSigma |
protected DenseVector |
userMu |
protected DenseVector |
userSigma |
protected DenseMatrix |
userTopicProbs |
burnIn, numItems, numIterations, numStats, numUsers, sampleLag
conf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, lastLoss, LOG, loss, maxRate, minRate, numRates, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose
Constructor and Description |
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GPLSARecommender() |
Modifier and Type | Method and Description |
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protected void |
eStep()
parameters estimation: used in the training phase
|
protected void |
mStep()
update the hyper-parameters
|
protected double |
predict(int userIdx,
int itemIdx)
predict a specific rating for user userIdx on item itemIdx, note that the
prediction is not bounded.
|
protected void |
setup()
setup
init member method
|
protected void |
trainModel()
train Model
|
estimateParams, isConverged, readoutParams
cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext
protected int numTopics
protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,java.util.Map<java.lang.Integer,java.lang.Double>> Q
protected DenseMatrix userTopicProbs
protected DenseMatrix topicItemMu
protected DenseMatrix topicItemSigma
protected DenseVector userMu
protected DenseVector userSigma
protected float smoothWeight
protected float b
protected static double smallValue
protected void setup() throws LibrecException
ProbabilisticGraphicalRecommender
setup
in class ProbabilisticGraphicalRecommender
LibrecException
- if error occurs during setting upprotected void trainModel() throws LibrecException
AbstractRecommender
trainModel
in class ProbabilisticGraphicalRecommender
LibrecException
- if error occurs during training modelprotected void eStep()
ProbabilisticGraphicalRecommender
eStep
in class ProbabilisticGraphicalRecommender
protected void mStep()
ProbabilisticGraphicalRecommender
mStep
in class ProbabilisticGraphicalRecommender
protected double predict(int userIdx, int itemIdx) throws LibrecException
AbstractRecommender
predict
in class AbstractRecommender
userIdx
- user indexitemIdx
- item indexLibrecException
- if error occurs during predictingCopyright © 2017. All Rights Reserved.