/**
* Copyright (C) 2001-2017 by RapidMiner and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapidminer.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.rvm;
/**
* Holds the RVM parameters
*
* @author Piotr Kasprzak, Ingo Mierswa
*
*/
public class Parameter {
// supported RVM types
private static class RVMType {
private String rvmType = null;
RVMType(String rvmType) {
this.rvmType = rvmType;
}
@Override
public String toString() {
return this.rvmType;
}
}
public final RVMType TYPE_REGRESSION = new RVMType("Regression-RVM");
public final RVMType TYPE_CLASSIFICATION = new RVMType("Classifictaion-RVM");
// the parameters to be chosen
public RVMType type = TYPE_REGRESSION;
public double min_delta_log_alpha = 1e-3; // Abort iteration if largest log alpha change is
// smaller than this
public double alpha_max = 1e12; // Prune basis function if its alpha is bigger than this
public int maxIterations = 10000; // Maximum number of iterations
public double initAlpha = 1.0; // Initial values for alpha_i hyperparameters
public double initSigma = 1.0; // Initial values for sigma = sqrt(variance)
}