net.librec.recommender.AbstractRecommender Maven / Gradle / Ivy
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/**
* Copyright (C) 2016 LibRec
*
* This file is part of LibRec.
* LibRec is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LibRec is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LibRec. If not, see userMappingData;
/**
* item Mapping Data
*/
public BiMap itemMappingData;
/**
* setup
*
* @throws LibrecException if error occurs during setup
*/
protected void setup() throws LibrecException {
conf = context.getConf();
isRanking = conf.getBoolean("rec.recommender.isranking");
if (isRanking) {
topN = conf.getInt("rec.recommender.ranking.topn", 10);
if (this.topN <= 0) {
throw new IndexOutOfBoundsException("rec.recommender.ranking.topn should be more than 0!");
}
}
earlyStop = conf.getBoolean("rec.recommender.earlystop", false);
verbose = conf.getBoolean("rec.recommender.verbose", true);
userMappingData = getDataModel().getUserMappingData();
itemMappingData = getDataModel().getItemMappingData();
if (verbose) {
progressBar = new ProgressBar(100, 100);
}
}
/**
* train Model
*
* @throws LibrecException if error occurs during training model
*/
protected abstract void trainModel() throws LibrecException;
/**
* recommend
*
* @param context recommender context
* @throws LibrecException if error occurs during recommending
*/
public void train(RecommenderContext context) throws LibrecException {
this.context = context;
setup();
LOG.info("Job Setup completed.");
trainModel();
LOG.info("Job Train completed.");
cleanup();
}
/**
* cleanup
*
* @throws LibrecException if error occurs during cleanup
*/
protected void cleanup() throws LibrecException {
}
/**
* (non-Javadoc)
*
* @see net.librec.recommender.Recommender#loadModel(String)
*/
@Override
public void loadModel(String filePath) {
}
/**
* (non-Javadoc)
*
* @see net.librec.recommender.Recommender#saveModel(String)
*/
@Override
public void saveModel(String filePath) {
}
/**
* get Context
*
* @return recommender context
*/
protected RecommenderContext getContext() {
return context;
}
/**
* set Context
*
* @param context recommender context
*/
public void setContext(RecommenderContext context) {
this.context = context;
}
/**
* get Data Model
*
* @return data model
*/
public DataModel getDataModel() {
return context.getDataModel();
}
/**
* get Recommended List
*
* @return Recommended List
*/
public List getRecommendedList(RecommendedList recommendedList) {
if (recommendedList != null && recommendedList.size() > 0) {
List userItemList = new ArrayList<>();
Iterator recommendedEntryIter = recommendedList.iterator();
if (userMappingData != null && userMappingData.size() > 0 && itemMappingData != null && itemMappingData.size() > 0) {
BiMap userMappingInverse = userMappingData.inverse();
BiMap itemMappingInverse = itemMappingData.inverse();
while (recommendedEntryIter.hasNext()) {
ContextKeyValueEntry contextKeyValueEntry = recommendedEntryIter.next();
if (contextKeyValueEntry != null) {
String userId = userMappingInverse.get(contextKeyValueEntry.getContextIdx());
String itemId = itemMappingInverse.get(contextKeyValueEntry.getKey());
if (StringUtils.isNotBlank(userId) && StringUtils.isNotBlank(itemId)) {
userItemList.add(new GenericRecommendedItem(userId, itemId, contextKeyValueEntry.getValue()));
}
}
}
return userItemList;
}
}
return null;
}
/**
* Post each iteration, we do things:
*
* - print debug information
* - check if converged
* - if not, adjust learning rate
*
*
* @param iter current iteration
* @return boolean: true if it is converged; false otherwise
* @throws LibrecException if error occurs
*/
protected boolean isConverged(int iter) throws LibrecException {
float delta_loss = (float) (lastLoss - loss);
// print out debug info
if (verbose) {
String recName = getClass().getSimpleName();
String info = recName + " iter " + iter + ": loss = " + loss + ", delta_loss = " + delta_loss;
LOG.info(info);
}
if (Double.isNaN(loss) || Double.isInfinite(loss)) {
// LOG.error("Loss = NaN or Infinity: current settings does not fit the recommender! Change the settings and try again!");
throw new LibrecException("Loss = NaN or Infinity: current settings does not fit the recommender! Change the settings and try again!");
}
// check if converged
return Math.abs(delta_loss) < 1e-5;
}
public void updateProgress(int currentPoint) {
if (verbose) {
conf.setInt("train.current.progress", currentPoint);
progressBar.showBarByPoint(conf.getInt("train.current.progress"));
}
}
}