/* * 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.util.normalize.output.zaxis; import org.encog.util.normalize.NormalizationError; import org.encog.util.normalize.input.InputField; import org.encog.util.normalize.output.OutputFieldGroup; import org.encog.util.normalize.output.OutputFieldGrouped; /** * Both the multiplicative and z-axis normalization types allow a group of * outputs to be adjusted so that the "vector length" is 1. Both go about it in * different ways. Certain types of neural networks require a vector length of * 1. * * Z-Axis normalization is usually a better choice than multiplicative. However, * multiplicative can perform better than Z-Axis when all of the values are near * zero most of the time. This can cause the "synthetic value" that z-axis uses * to dominate and skew the answer. * * Z-Axis gets its name from 3D computer graphics, where there is a Z-Axis * extending from the plane created by the X and Y axes. It has nothing to do * with z-scores or the z-transform of signal theory. * * To implement Z-Axis normalization a scaling factor must be created to * multiply each of the inputs against. Additionally, a synthetic field must be * added. It is very important that this synthetic field be added to any z-axis * group that you might use. The synthetic field is represented by the * OutputFieldZAxisSynthetic class. * * @author jheaton */ public class OutputFieldZAxis extends OutputFieldGrouped { /** * Construct a ZAxis output field. * @param group The group this field belongs to. * @param field The input field this is based on. */ public OutputFieldZAxis(final OutputFieldGroup group, final InputField field) { super(group, field); if (!(group instanceof ZAxisGroup)) { throw new NormalizationError( "Must use ZAxisGroup with OutputFieldZAxis."); } } /** * Calculate the current value for this field. * * @param subfield * Ignored, this field type does not have subfields. * @return The current value for this field. */ public double calculate(final int subfield) { return (getSourceField().getCurrentValue() * ((ZAxisGroup) getGroup()) .getMultiplier()); } /** * @return The subfield count, which is one, as this field type does not * have subfields. */ public int getSubfieldCount() { return 1; } /** * Not needed for this sort of output field. */ public void rowInit() { } }