public class RBMRecommender extends AbstractRecommender
The origin paper:
Salakhutdinov, R., Mnih, A. Hinton, G, Restricted BoltzmanMachines for Collaborative Filtering, To appear inProceedings of the 24thInternational Conference onMachine Learning 2007. http://www.cs.toronto.edu/~rsalakhu/papers/rbmcf.pdf
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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RBMRecommender() |
Modifier and Type | Method and Description |
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protected double |
predict(int u,
int m)
predict a specific rating for user userIdx on item itemIdx, note that the
prediction is not bounded.
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protected void |
setup()
setup
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protected void |
trainModel()
train Model
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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 u, int m) throws LibrecException
AbstractRecommender
predict
in class AbstractRecommender
u
- user indexm
- item indexLibrecException
- if error occurs during predictingCopyright © 2017. All Rights Reserved.