/* * Encog(tm) Core v3.4 - Java Version * http://www.heatonresearch.com/encog/ * https://github.com/encog/encog-java-core * Copyright 2008-2016 Heaton Research, Inc. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package org.encog.neural.som.training.basic.neighborhood; /** * Defines how a neighborhood function should work in competitive training. This * is most often used in the training process for a self-organizing map. This * function determines to what degree the training should take place on a * neuron, based on its proximity to the "winning" neuron. * * @author jheaton * */ public interface NeighborhoodFunction { /** * Determine how much the current neuron should be affected by training * based on its proximity to the winning neuron. * * @param currentNeuron * THe current neuron being evaluated. * @param bestNeuron * The winning neuron. * @return The ratio for this neuron's adjustment. */ double function(int currentNeuron, int bestNeuron); /** * @return The radius. */ double getRadius(); /** * Set the radius. * @param radius The new radius. */ void setRadius(double radius); }