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.matlib.regul;
031
032import ch.akuhn.matrix.Matrix;
033import ch.akuhn.matrix.Vector;
034import ch.akuhn.matrix.Vector.Entry;
035
036
037/**
038 *
039 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
040 */
041public class L1Regulariser implements Regulariser{
042
043        @Override
044        public Matrix prox(Matrix W, double lambda) {
045                return softThreshold(W,lambda);
046        }
047
048        private Matrix softThreshold(Matrix w, double lambda) {
049                Matrix ret = w.newInstance();
050                
051                int rowi = 0;
052                for (Vector row : w.rows()) {
053                        for (Entry ent : row.entries()) {
054                                if(ent.value < -lambda){
055                                        ret.put(rowi, ent.index, ent.value + lambda);
056                                }
057                                else if(ent.value > lambda){
058                                        ret.put(rowi, ent.index, ent.value - lambda);
059                                }
060                        }
061                        rowi++;
062                }
063                return ret;
064        }
065        
066        
067
068}