public class BHFreeRecommender extends ProbabilisticGraphicalRecommender
Remarks: this class implements the BH-free method.
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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BHFreeRecommender() |
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 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 double |
predictRanking(int userIdx,
int itemIdx) |
protected double |
predictRating(int userIdx,
int itemIdx) |
protected void |
readoutParams()
read out parameters for each iteration
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protected void |
setup()
setup
init member method
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isConverged, trainModel
cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext
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 void readoutParams()
ProbabilisticGraphicalRecommender
readoutParams
in class ProbabilisticGraphicalRecommender
protected void estimateParams()
ProbabilisticGraphicalRecommender
estimateParams
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 predictingprotected double predictRating(int userIdx, int itemIdx)
protected double predictRanking(int userIdx, int itemIdx)
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