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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
/*
* 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 .
*/
/*
* RegressionGenerator.java
* Copyright (C) 2005-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.datagenerators;
import java.util.Collections;
import java.util.Enumeration;
import java.util.Vector;
import weka.core.Option;
import weka.core.Utils;
/**
* Abstract class for data generators for regression classifiers.
*
*
* Example usage as the main of a datagenerator called RandomGenerator:
*
*
* public static void main(String[] args) {
* try {
* DataGenerator.makeData(new RandomGenerator(), args);
* } catch (Exception e) {
* e.printStackTrace();
* System.err.println(e.getMessage());
* }
* }
*
*
* @author FracPete (fracpete at waikato dot ac dot nz)
* @version $Revision: 10203 $
*/
public abstract class RegressionGenerator extends DataGenerator {
/** for serialization */
private static final long serialVersionUID = 3073254041275658221L;
/** Number of instances */
protected int m_NumExamples;
/**
* initializes the generator with default values
*/
public RegressionGenerator() {
super();
setNumExamples(defaultNumExamples());
}
/**
* Returns an enumeration describing the available options.
*
* @return an enumeration of all the available options.
*/
@Override
public Enumeration