/*
* 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.mf.funksvd;
import it.unimi.dsi.fastutil.doubles.DoubleArrayList;
import it.unimi.dsi.fastutil.doubles.DoubleList;
import it.unimi.dsi.fastutil.doubles.DoubleLists;
import java.io.Serializable;
/**
* Information about a feature.
*
* @author <a href="http://www.grouplens.org">GroupLens Research</a>
* @since 1.1
*/
public class FeatureInfo implements Serializable {
private static final long serialVersionUID = 1L;
private final int feature;
private final double userAverage;
private final double itemAverage;
private final double singularValue;
private final DoubleList trainingErrors;
private FeatureInfo(int f, double uavg, double iavg, double sval,
DoubleList errors) {
feature = f;
userAverage = uavg;
itemAverage = iavg;
singularValue = sval;
trainingErrors = new DoubleArrayList(errors);
}
//region Getters
/**
* Get the feature number.
*
* @return The feature number.
*/
public int getFeature() {
return feature;
}
/**
* Get the iteration count for the feature.
*
* @return The number of iterations used to train the feature.
*/
public int getIterCount() {
return trainingErrors.size();
}
/**
* Get the training error for each iteration.
* @return The training error for each iteration.
*/
public DoubleList getTrainingErrors() {
return DoubleLists.unmodifiable(trainingErrors);
}
/**
* Get the last training RMSE of the feature.
*
* @return The RMSE of the last iteration training this feature.
*/
public double getLastRMSE() {
return trainingErrors.getDouble(trainingErrors.size() - 1);
}
/**
* Get the last delta RMSE of the feature.
*
* @return The RMSE improvement in the last training round of this feature.
*/
public double getLastDeltaRMSE() {
int n = trainingErrors.size();
return trainingErrors.getDouble(n-2) - trainingErrors.getDouble(n-1);
}
/**
* Get the user average value of this feature.
*
* @return The user average value.
*/
public double getUserAverage() {
return userAverage;
}
/**
* Get the item average value of this feature.
*
* @return The item average value.
*/
public double getItemAverage() {
return itemAverage;
}
/**
* Get the singular value of this feature.
*
* @return The singular value (weight) of the feature.
*/
public double getSingularValue() {
return singularValue;
}
//endregion
/**
* Helper class to build feature info.
*/
public static class Builder implements org.apache.commons.lang3.builder.Builder<FeatureInfo> {
private final int feature;
private double userAverage;
private double itemAverage;
private double singularValue;
private DoubleList trainingError = new DoubleArrayList();
/**
* Construct a new builder.
* @param f The feature number.
*/
public Builder(int f) {
feature = f;
}
/**
* Get the feature's number.
* @return The feature's number.
*/
public int getFeature() {
return feature;
}
@Override
public FeatureInfo build() {
return new FeatureInfo(feature, userAverage, itemAverage, singularValue, trainingError);
}
public double getUserAverage() {
return userAverage;
}
public Builder setUserAverage(double userAverage) {
this.userAverage = userAverage;
return this;
}
public double getItemAverage() {
return itemAverage;
}
public Builder setItemAverage(double itemAverage) {
this.itemAverage = itemAverage;
return this;
}
public double getSingularValue() {
return singularValue;
}
/**
* Set the singular value for this feature.
* @param singularValue The feature's singular value.
* @return The builder (for chaining).
*/
public Builder setSingularValue(double singularValue) {
this.singularValue = singularValue;
return this;
}
/**
* Add the error for a training round.
* @param err The error for the training round.
* @return The builder (for chaining).
*/
public Builder addTrainingRound(double err) {
trainingError.add(err);
return this;
}
}
}