PNNOutputMode.java

/*
 * 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:
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 */
package org.encog.neural.pnn;

/**
 * The output mode that will be used by the PNN.
 */
public enum PNNOutputMode {
	/**
	 * Unsupervised training will make use of autoassociation. No "ideal" values
	 * should be provided for training. Input and output neuron counts must
	 * match.
	 */
	Unsupervised,

	/**
	 * Regression is where the neural network performs as a function. Input is
	 * supplied, and output is returned. The output is a numeric value.
	 */
	Regression,

	/**
	 * Classification attempts to classify the input into a number of predefined
	 * classes. The class is stored in the ideal as a single "double" value,
	 * though it is really treated as an integer that represents class
	 * membership. The number of output neurons should match the number of
	 * classes. Classes are indexed beginning at 0.
	 */
	Classification
}