//
// Encog(tm) Core v3.3 - .Net Version
// http://www.heatonresearch.com/encog/
//
// Copyright 2008-2014 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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namespace Encog.ML.Train.Strategy
{
    /// <summary>
    /// Training strategies can be added to training algorithms.  Training 
    /// strategies allow different additional logic to be added to an existing
    /// training algorithm.  There are a number of different training strategies
    /// that can perform various tasks, such as adjusting the learning rate or 
    /// momentum, or terminating training when improvement diminishes.  Other 
    /// strategies are provided as well.
    /// </summary>
    ///
    public interface IStrategy
    {
        /// <summary>
        /// Initialize this strategy.
        /// </summary>
        ///
        /// <param name="train">The training algorithm.</param>
        void Init(IMLTrain train);

        /// <summary>
        /// Called just before a training iteration.
        /// </summary>
        ///
        void PreIteration();

        /// <summary>
        /// Called just after a training iteration.
        /// </summary>
        ///
        void PostIteration();
    }
}
