/*
* LensKit, an open source recommender systems toolkit.
* Copyright 2010-2014 LensKit Contributors. See CONTRIBUTORS.md.
* Work on LensKit has been funded by the National Science Foundation under
* grants IIS 05-34939, 08-08692, 08-12148, and 10-17697.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2.1 of the
* License, or (at your option) any later version.
*
* This program 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
* this program; if not, write to the Free Software Foundation, Inc., 51
* Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
package org.grouplens.lenskit.transform.quantize;
import it.unimi.dsi.fastutil.longs.LongSet;
import org.grouplens.lenskit.ItemScorer;
import org.grouplens.lenskit.RatingPredictor;
import org.grouplens.lenskit.baseline.BaselineScorer;
import org.grouplens.lenskit.baseline.PrimaryScorer;
import org.grouplens.lenskit.basic.AbstractRatingPredictor;
import org.grouplens.lenskit.vectors.MutableSparseVector;
import org.grouplens.lenskit.vectors.SparseVector;
import org.grouplens.lenskit.vectors.VectorEntry;
import javax.annotation.Nonnull;
import javax.annotation.Nullable;
import javax.inject.Inject;
/**
* A rating predictor wrapper that quantizes predictions.
* @author <a href="http://www.grouplens.org">GroupLens Research</a>
*/
public class QuantizedRatingPredictor extends AbstractRatingPredictor implements RatingPredictor {
private final ItemScorer itemScorer;
private final ItemScorer baselineScorer;
private final Quantizer quantizer;
/**
* Construct a new quantized predictor.
* @param scorer The item scorer to use.
* @param baseline A baseline scorer to fall back to.
* @param q The quantizer.
*/
@Inject
public QuantizedRatingPredictor(@PrimaryScorer ItemScorer scorer,
@Nullable @BaselineScorer ItemScorer baseline,
Quantizer q) {
itemScorer = scorer;
baselineScorer = baseline;
quantizer = q;
}
private void quantize(MutableSparseVector scores) {
for (VectorEntry e: scores) {
scores.set(e, quantizer.getIndexValue(quantizer.index(e.getValue())));
}
}
@Override
public void predict(long user, @Nonnull MutableSparseVector scores) {
itemScorer.score(user, scores);
if (baselineScorer != null) {
LongSet unset = scores.unsetKeySet();
if (!unset.isEmpty()) {
SparseVector bscores = baselineScorer.score(user, unset);
scores.set(bscores);
}
}
quantize(scores);
}
}