/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
package keel.Algorithms.Neural_Networks.NNEP_Common;
import keel.Algorithms.Neural_Networks.NNEP_Common.neuralnet.INeuralNet;
import net.sf.jclec.ISpecies;
import net.sf.jclec.util.range.Interval;
/**
* <p>
* @author Written by Pedro Antonio Gutierrez Penia (University of Cordoba) 16/7/2007
* @param <I> Type of represented individuals
* @version 0.1
* @since JDK1.5
* </p>
*/
public interface INeuralNetSpecies<I extends NeuralNetIndividual> extends ISpecies<I>
{
/**
* <p>
* Species for Individuals that contains a NeuralNet as genotype.
* </p>
*/
// Factory methods
/**
* <p>
* Factory method
*
* @param genotype Individual genotype
*
* @return I A new instance of represented class
* </p>
*/
public I createIndividual(INeuralNet genotype);
/**
* <p>
* Factory method
*
* @return I A new instance of individual genotype
* </p>
*/
public INeuralNet createGenotype();
// Genotype information
/**
* <p>
* Returns number of hidden layers of the neural nets
*
* @return int Number of hidden layers
* </p>
*/
public int getNOfHiddenLayers();
/**
* <p>
* Returns number of inputs of the neural nets
*
* @return int Number of inputs
* </p>
*/
public int getNOfInputs();
/**
* <p>
* Returns number of outputs of the neural nets
*
* @return int Number of outputs
* </p>
*/
public int getNOfOutputs();
/**
* <p>
* Returns weight range of a hidden layer
*
* @param index Index of the desired hidden layer
* @param indexRange Index of the desired range into the layer (useful for hibrid layer)
*
* @return Interval Weight range
* </p>
*/
public Interval getHiddenLayerWeightRange(int index, int indexRange);
/**
* <p>
* Returns weight range of the output layer
*
* @param indexRange Index of the desired range into the layer (useful for hibrid layer)
*
* @return Interval Weight range
* </p>
*/
public Interval getOutputLayerWeightRange(int indexRange);
/**
* <p>
* Returns maximum number of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return int Maximum number of neurons
* </p>
*/
public int getHiddenLayerMaxNofneurons(int index);
/**
* <p>
* Returns minimum number of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return int Minimum number of neurons
* </p>
*/
public int getHiddenLayerMinNofneurons(int index);
/**
* <p>
* Returns initial maximum number of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return int Initial maximum number of neurons
* </p>
*/
public int getHiddenLayerInitialMaxNofneurons(int index);
/**
* <p>
* Returns type of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return String Type of neurons
* </p>
*/
public String getHiddenLayerType(int index);
/**
* <p>
* Returns type of neurons of the output layer
*
* @return String Type of neurons
* </p>
*/
public String getOutputLayerType();
/**
* <p>
* Returns initiator of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return String Initiator of neurons
* </p>
*/
public String getHiddenLayerInitiator(int index);
/**
* <p>
* Returns initiator of neurons of the output layer
*
* @return String Initiator of neurons
* </p>
*/
public String getOutputLayerInitiator();
/**
* <p>
* Returns a boolean indicating if a hidden layer is biased
*
* @param index Index of the desired hidden layer
*
* @return boolean Is hidden layer biased?
* </p>
*/
public boolean isHiddenLayerBiased(int index);
/**
* <p>
* Returns a boolean indicating if output layer is biased
*
* @return boolean Is output layer biased?
* </p>
*/
public boolean isOutputLayerBiased();
/**
* <p>
* Returns an array of neuron types of a concrete layer
*
* @param index Index of the desired hidden layer
*
* @return String[] Array of neurons types
* </p>
*/
public String[] getNeuronTypes(int index);
/**
* <p>
* Returns an array of percentages of a concrete layer
* for an hibrid layer
*
* @param index Index of the desired hidden layer
*
* @return double[] Array of percentages
* </p>
*/
public double[] getPercentages(int index);
/**
* <p>
* Returns an array of initiators of neurons of hibrid layers
*
* @param index Index of the desired hidden layer
*
* @return String[] Array of percentages
* </p>
*/
public String[] getInitiatorNeuronTypes(int index);
}