MethodConfig.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:
 * http://www.heatonresearch.com/copyright
 */
package org.encog.ml.model.config;

import org.encog.ml.data.versatile.VersatileMLDataSet;
import org.encog.ml.data.versatile.normalizers.strategies.NormalizationStrategy;

/**
 * Define normalization for a specific method.
 */
public interface MethodConfig {

	/**
	 * @return The method name.
	 */
	String getMethodName();

	/**
	 * Suggest a model architecture, based on a dataset.
	 * @param dataset The dataset.
	 * @return The model architecture.
	 */
	String suggestModelArchitecture(VersatileMLDataSet dataset);

	/**
	 * Suggest a normalization strategy based on a dataset.
	 * @param dataset The dataset.
	 * @param architecture The architecture.
	 * @return The strategy.
	 */
	NormalizationStrategy suggestNormalizationStrategy(VersatileMLDataSet dataset, String architecture);

	/**
	 * Suggest a training type.
	 * @return The training type.
	 */
	String suggestTrainingType();

	/**
	 * Suggest training arguments.
	 * @param trainingType The training type.
	 * @return The training arguments.
	 */
	String suggestTrainingArgs(String trainingType);

	/**
	 * Determine the needed output count.
	 * @param dataset The dataset.
	 * @return The needed output count.
	 */
	int determineOutputCount(VersatileMLDataSet dataset);

}