public class UserAverageRecommender extends AbstractRecommender
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 |
---|
UserAverageRecommender() |
Modifier and Type | Method and Description |
---|---|
protected double |
predict(int userIdx,
int itemIdx)
the user ratings average value as the predictive rating for user userIdx on item itemIdx.
|
protected void |
setup()
setup
|
protected void |
trainModel()
train Model
|
cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext
protected void setup() throws LibrecException
AbstractRecommender
setup
in class AbstractRecommender
LibrecException
- if error occurs during setupprotected void trainModel() throws LibrecException
AbstractRecommender
trainModel
in class AbstractRecommender
LibrecException
- if error occurs during training modelprotected double predict(int userIdx, int itemIdx) throws LibrecException
predict
in class AbstractRecommender
userIdx
- user indexitemIdx
- item indexLibrecException
- if error occurs during predictingCopyright © 2017. All Rights Reserved.