/*
* RapidMiner
*
* Copyright (C) 2001-2008 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.learner.functions.kernel.gaussianprocess;
/**
* Holds the GP parameters
*
* @author Piotr Kasprzak
* @version $Id: Parameter.java,v 1.3 2008/05/09 19:23:17 ingomierswa Exp $
*
*/
public class Parameter {
// supported GP types
private static class GPType {
private String gpType = null;
GPType(String gpType) {
this.gpType = gpType;
}
public String toString() {
return this.gpType;
}
}
public static final GPType TYPE_GAUSS_REGRESSION = new GPType("Regression");
/** The parameters to be chosen */
/* Type of the GP Learner */
public GPType type = TYPE_GAUSS_REGRESSION;
/* Maximum number of basis vectors to use */
public int maxBasisVectors = 100;
/*
* Tolerance value: we project the current basis vector if it has a orthogonal distance to the linear span of the
* other basis vectors smaller than epsilon_tol
*/
public double epsilon_tol = 1e-7;
public double geometrical_tol = 1e-7;
}