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 * An implementation of a simple {@link KernelPerceptron} which works with
036 * double array inputs and is binary.
037 *
038 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
039 */
040public class ThresholdDoubleArrayKernelPerceptron extends DoubleArrayKernelPerceptron {
041
042        private double rate;
043        private double thresh;
044
045        public ThresholdDoubleArrayKernelPerceptron(VectorKernel k) {
046                this(0.1, 0, k);
047        }
048
049        public ThresholdDoubleArrayKernelPerceptron(double weight, double threshold, VectorKernel k) {
050                super(k);
051                this.rate = weight;
052                this.thresh = threshold;
053
054        }
055
056        @Override
057        public PerceptronClass predict(double[] x) {
058                double apply = mapping(x);
059                if (Math.abs(apply) < this.thresh)
060                        apply = -1;
061                return PerceptronClass.fromSign(Math.signum(apply));
062
063        }
064
065        @Override
066        double getUpdateRate() {
067                return rate;
068        }
069
070}