/*
 * LensKit, an open source recommender systems toolkit.
 * Copyright 2010-2013 Regents of the University of Minnesota and contributors
 * 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 java.io.Serializable;

/**
 * Information about a feature.
 *
 * @author <a href="http://www.grouplens.org">GroupLens Research</a>
 */
public class FeatureInfo implements Serializable {
    private static final long serialVersionUID = 1L;

    private final double userAverage;
    private final double itemAverage;
    private final int iterCount;
    private final double lastRMSE;
    private final double lastDeltaRMSE;

    public FeatureInfo(double uavg, double iavg, int niters, double rmse, double delta) {
        userAverage = uavg;
        itemAverage = iavg;
        iterCount = niters;
        lastRMSE = rmse;
        lastDeltaRMSE = delta;
    }

    /**
     * Get the iteration count for the feature.
     *
     * @return The number of iterations used to train the feature.
     */
    public int getIterCount() {
        return iterCount;
    }

    /**
     * Get the last training RMSE of the feature.
     *
     * @return The RMSE of the last iteration training this feature.
     */
    public double getLastRMSE() {
        return lastRMSE;
    }

    /**
     * Get the last delta RMSE of the feature.
     *
     * @return The RMSE improvement in the last training round of this feature.
     */
    public double getLastDeltaRMSE() {
        return lastDeltaRMSE;
    }

    /**
     * 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;
    }
}

/*
 * LensKit, an open source recommender systems toolkit.
 * Copyright 2010-2013 Regents of the University of Minnesota and contributors
 * 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 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 double userAverage;
    private final double itemAverage;
    private final int iterCount;
    private final double lastRMSE;
    private final double lastDeltaRMSE;

    public FeatureInfo(double uavg, double iavg, int niters, double rmse, double delta) {
        userAverage = uavg;
        itemAverage = iavg;
        iterCount = niters;
        lastRMSE = rmse;
        lastDeltaRMSE = delta;
    }

    /**
     * Get the iteration count for the feature.
     *
     * @return The number of iterations used to train the feature.
     */
    public int getIterCount() {
        return iterCount;
    }

    /**
     * Get the last training RMSE of the feature.
     *
     * @return The RMSE of the last iteration training this feature.
     */
    public double getLastRMSE() {
        return lastRMSE;
    }

    /**
     * Get the last delta RMSE of the feature.
     *
     * @return The RMSE improvement in the last training round of this feature.
     */
    public double getLastDeltaRMSE() {
        return lastDeltaRMSE;
    }

    /**
     * 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;
    }
}

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