001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.math.model.fit;
031
032import java.util.List;
033
034import org.openimaj.math.model.Model;
035import org.openimaj.util.pair.IndependentPair;
036
037/**
038 * An interface that describes an object capable of fitting data to a model in a
039 * more generic way than through the Model's estimate method.
040 * 
041 * @author Jonathon Hare
042 * 
043 * @param <I>
044 *            type of independent data
045 * @param <D>
046 *            type of dependent data
047 * @param <M>
048 *            concrete type of model learned
049 */
050public interface ModelFitting<I, D, M extends Model<I, D>> {
051        /**
052         * Attempt to fit the given data to the model.
053         * 
054         * @param data
055         *            Data to be fitted
056         * @return true on success, false otherwise
057         */
058        boolean fitData(List<? extends IndependentPair<I, D>> data);
059
060        /**
061         * @return The minimum number of observations required to estimate the
062         *         model.
063         */
064        public int numItemsToEstimate();
065
066        /**
067         * @return the trained model object
068         */
069        M getModel();
070}