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.ml.linear.learner.perceptron;
031
032import org.openimaj.ml.linear.kernel.VectorKernel;
033
034/**
035 *
036 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
037 */
038public class MarginMeanCenteredPerceptron extends MeanCenteredKernelPerceptron{
039
040        private static final double DEFAULT_MARGIN = 0.1;
041        private double margin = DEFAULT_MARGIN;
042
043        /**
044         * @param kernel
045         * @param margin
046         */
047        public MarginMeanCenteredPerceptron(VectorKernel kernel, double margin) {
048                super(kernel);
049                this.margin = margin;
050        }
051        /**
052         * @param kernel
053         */
054        public MarginMeanCenteredPerceptron(VectorKernel kernel) {
055                super(kernel);
056        }
057        
058        @Override
059        public void process(double[] xt, PerceptronClass yt) {
060                double val = mapping(xt);
061                PerceptronClass yt_prime = PerceptronClass.fromSign(Math.signum(val));
062                if(!yt_prime.equals(yt) || Math.abs(val) < margin){
063                        update(xt,yt,yt_prime);
064                        this.errors ++;
065                }
066        }
067}