public class PLSARecommender extends ProbabilisticGraphicalRecommender
Modifier and Type | Field and Description |
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protected DenseVector |
numItemsRateByUser
entry[u]: number of tokens rated by user u.
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protected int |
numTopics
number of latent topics
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protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,double[]> |
Q
{user, item, {topic z, probability}}
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protected DenseMatrix |
topicItemProbs
Conditional Probability: P(i|z)
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protected DenseMatrix |
topicItemProbsSum
Conditional Probability: P(i|z)
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protected DenseMatrix |
userTopicProbs
Conditional Probability: P(z|u)
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protected DenseMatrix |
userTopicProbsSum
Conditional Probability: P(z|u)
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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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PLSARecommender() |
Modifier and Type | Method and Description |
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protected void |
eStep()
parameters estimation: used in the training phase
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protected void |
mStep()
update the hyper-parameters
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protected double |
predict(int userIdx,
int itemIdx)
predict a specific rating for user userIdx on item itemIdx, note that the
prediction is not bounded.
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protected void |
setup()
setup
init member method
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estimateParams, isConverged, readoutParams, trainModel
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,double[]> Q
protected DenseMatrix userTopicProbs
protected DenseMatrix userTopicProbsSum
protected DenseMatrix topicItemProbs
protected DenseMatrix topicItemProbsSum
protected DenseVector numItemsRateByUser
protected void setup() throws LibrecException
ProbabilisticGraphicalRecommender
setup
in class ProbabilisticGraphicalRecommender
LibrecException
- if error occurs during setting upprotected 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.