public class ItemClusterRecommender extends ProbabilisticGraphicalRecommender
UserCluster
recommender.burnIn, numItems, numIterations, numStats, numUsers, sampleLag
conf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, LOG, loss, maxRate, minRate, numRates, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose
Constructor and Description |
---|
ItemClusterRecommender() |
Modifier and Type | Method and Description |
---|---|
protected void |
eStep()
parameters estimation: used in the training phase
|
protected boolean |
isConverged(int iter)
Post each iteration, we do things:
print debug information
check if converged
if not, adjust learning rate
|
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
|
estimateParams, readoutParams, 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 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.