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/*
 * Encog(tm) Core v3.4 - Java Version
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-core
 
 * Copyright 2008-2017 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.ml;

/**
 * This is a convenience interface that combines MLInput and MLOutput.  
 * Together these define a MLMethod that both accepts input and 
 * produces output.
 * 
 * Input and output are defined as a simple array of double values.  
 * Many machine learning methods, such as neural networks and 
 * support vector machines handle input and output in this way, 
 * and thus implement this interface.  Others, such as clustering, 
 * do not.
 *
 */
public interface MLInputOutput extends MLInput, MLOutput {

}