public class URPRecommender extends ProbabilisticGraphicalRecommender
Benjamin Marlin, Modeling user rating profiles for collaborative filtering, NIPS 2003.
Nicola Barbieri, Regularized gibbs sampling for user profiling with soft constraints, ASONAM 2011.
Modifier and Type | Field and Description |
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protected int |
numRatingLevels |
protected int |
numTopics
number of topics
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protected double[][][] |
topicItemRatingProbs
posterior probabilities of parameters phi_{k, i, r}
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protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,java.lang.Integer> |
topics |
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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URPRecommender() |
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 |
estimateParams()
estimate the model parameters
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protected boolean |
isConverged(int iter)
Post each iteration, we do things:
print debug information
check if converged
if not, adjust learning rate
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protected void |
mStep()
Thomas P.
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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 |
readoutParams()
read out parameters for each iteration
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protected void |
setup()
setup
init member method
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trainModel
cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext
protected com.google.common.collect.Table<java.lang.Integer,java.lang.Integer,java.lang.Integer> topics
protected int numTopics
protected int numRatingLevels
protected double[][][] topicItemRatingProbs
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()
mStep
in class ProbabilisticGraphicalRecommender
protected void readoutParams()
ProbabilisticGraphicalRecommender
readoutParams
in class ProbabilisticGraphicalRecommender
protected void estimateParams()
ProbabilisticGraphicalRecommender
estimateParams
in class ProbabilisticGraphicalRecommender
protected boolean isConverged(int iter)
AbstractRecommender
isConverged
in class ProbabilisticGraphicalRecommender
iter
- current iterationprotected 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.