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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 .
*/
/*
* Puk.java
* Copyright (C) 2007-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.classifiers.functions.supportVector;
import java.util.Collections;
import java.util.Enumeration;
import java.util.Vector;
import weka.core.Capabilities;
import weka.core.Capabilities.Capability;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Option;
import weka.core.RevisionUtils;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;
import weka.core.TechnicalInformationHandler;
import weka.core.Utils;
/**
* The Pearson VII function-based universal kernel.
*
* For more information see:
*
* B. Uestuen, W.J. Melssen, L.M.C. Buydens (2006). Facilitating the application
* of Support Vector Regression by using a universal Pearson VII function based
* kernel. Chemometrics and Intelligent Laboratory Systems. 81:29-40.
*
*
*
* Valid options are:
*
*
*
* -D
* Enables debugging output (if available) to be printed.
* (default: off)
*
*
*
* -no-checks
* Turns off all checks - use with caution!
* (default: checks on)
*
*
*
* -C <num>
* The size of the cache (a prime number), 0 for full cache and
* -1 to turn it off.
* (default: 250007)
*
*
*
* -O <num>
* The Omega parameter.
* (default: 1.0)
*
*
*
* -S <num>
* The Sigma parameter.
* (default: 1.0)
*
*
*
*
* @author Bernhard Pfahringer ([email protected])
* @version $Revision: 10169 $
*/
public class Puk extends CachedKernel implements TechnicalInformationHandler {
/** for serialization */
private static final long serialVersionUID = 1682161522559978851L;
/** The precalculated dotproducts of <inst_i,inst_i> */
protected double m_kernelPrecalc[];
/** Omega for the Puk kernel. */
protected double m_omega = 1.0;
/** Sigma for the Puk kernel. */
protected double m_sigma = 1.0;
/** Cached factor for the Puk kernel. */
protected double m_factor = 1.0;
/**
* default constructor - does nothing.
*/
public Puk() {
super();
}
/**
* Constructor. Initializes m_kernelPrecalc[].
*
* @param data the data to use
* @param cacheSize the size of the cache
* @param omega the exponent
* @param sigma the bandwidth
* @throws Exception if something goes wrong
*/
public Puk(Instances data, int cacheSize, double omega, double sigma) throws Exception {
super();
setCacheSize(cacheSize);
setOmega(omega);
setSigma(sigma);
buildKernel(data);
}
/**
* Returns a string describing the kernel
*
* @return a description suitable for displaying in the explorer/experimenter
* gui
*/
@Override
public String globalInfo() {
return "The Pearson VII function-based universal kernel.\n\n"
+ "For more information see:\n\n" + getTechnicalInformation().toString();
}
/**
* Returns an instance of a TechnicalInformation object, containing detailed
* information about the technical background of this class, e.g., paper
* reference or book this class is based on.
*
* @return the technical information about this class
*/
@Override
public TechnicalInformation getTechnicalInformation() {
TechnicalInformation result;
result = new TechnicalInformation(Type.ARTICLE);
result.setValue(Field.AUTHOR,
"B. Uestuen and W.J. Melssen and L.M.C. Buydens");
result.setValue(Field.YEAR, "2006");
result
.setValue(
Field.TITLE,
"Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel");
result.setValue(Field.JOURNAL,
"Chemometrics and Intelligent Laboratory Systems");
result.setValue(Field.VOLUME, "81");
result.setValue(Field.PAGES, "29-40");
result.setValue(Field.PDF,
"http://www.cac.science.ru.nl/research/publications/PDFs/ustun2006.pdf");
return result;
}
/**
* Returns an enumeration describing the available options.
*
* @return an enumeration of all the available options.
*/
@Override
public Enumeration
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