Java tutorial
/* * Copyright (c) [2016-2017] [University of Minnesota] * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in all * copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ package org.grouplens.samantha.modeler.solver; import org.apache.commons.math3.linear.RealVector; import java.util.ArrayList; import java.util.List; /** * @author <a href="http://www.grouplens.org">GroupLens Research</a> */ public class L2Regularizer implements Regularizer { public L2Regularizer() { } public double getValue(double var) { return var * var; } public double getGradient(double var) { return 2 * var; } public RealVector addGradient(RealVector grad, RealVector var, double l2coef) { return grad.combineToSelf(1.0, 2 * l2coef, var); } public double getObjective(double l2coef, RealVector var) { double l2norm = var.getNorm(); return l2coef * l2norm * l2norm; } public double getObjective(double l2coef, List<RealVector> vars) { double objVal = 0.0; for (RealVector realVector : vars) { double l2norm = realVector.getNorm(); objVal += l2norm * l2norm; } return objVal * l2coef; } }