@ModelData(value={"isRanking","prankd","userFactors","itemFactors","trainMatrix"}) public class PRankDRecommender extends RankSGDRecommender
Related Work:
itemProbs
initMean, initStd, itemFactors, learnRate, maxLearnRate, numFactors, numIterations, regItem, regUser, userFactors
conf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, lastLoss, LOG, loss, maxRate, minRate, numItems, numRates, numUsers, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose
Constructor and Description |
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PRankDRecommender() |
Modifier and Type | Method and Description |
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protected void |
setup()
initialization
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protected void |
trainModel()
train model
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predict, updateLRate
cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext
protected void setup() throws LibrecException
setup
in class RankSGDRecommender
LibrecException
- if error occursprotected void trainModel() throws LibrecException
trainModel
in class RankSGDRecommender
LibrecException
- if error occursCopyright © 2017. All Rights Reserved.