@ModelData(value={"isRating","sorec","userFactors","itemFactors"}) public class SoRecRecommender extends SocialRecommender
regSocial, socialMatrix
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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SoRecRecommender() |
Modifier and Type | Method and Description |
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void |
setup()
setup
init member method
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protected void |
trainModel()
train Model
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denormalize, normalize, predict
predict, updateLRate
cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, recommend, recommend, recommendRank, recommendRating, saveModel, setContext
public void setup() throws LibrecException
MatrixFactorizationRecommender
setup
in class SocialRecommender
LibrecException
- if error occurs during setting upprotected void trainModel() throws LibrecException
AbstractRecommender
trainModel
in class AbstractRecommender
LibrecException
- if error occurs during training modelCopyright © 2017. All Rights Reserved.