/*
* 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.
*
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* and trademarks visit:
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*/
package org.encog.neural.networks.training;
/**
* Specifies that a training algorithm has the concept of a learning rate.
* This allows it to be used with strategies that automatically adjust the
* learning rate.
*
* @author jheaton
*
*/
public interface LearningRate {
/**
* Set the learning rate.
* @param rate The new learning rate
*/
void setLearningRate(double rate);
/**
* @return The learning rate.
*/
double getLearningRate();
}