/*
* 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.postprocessing;
import java.util.List;
import com.rapidminer.operator.IOObject;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeDouble;
import com.rapidminer.parameter.ParameterTypeString;
/**
* This operator creates a user defined threshold for crisp classifying based on
* prediction confidences.
*
* @author Ingo Mierswa
* @version $Id: ThresholdCreator.java,v 1.5 2008/07/07 07:06:46 ingomierswa Exp $
*/
public class ThresholdCreator extends Operator {
/** The parameter name for "The confidence threshold to determine if the prediction should be positive." */
public static final String PARAMETER_THRESHOLD = "threshold";
/** The parameter name for "The class which should be considered as the first one (confidence 0)." */
public static final String PARAMETER_FIRST_CLASS = "first_class";
/** The parameter name for "The class which should be considered as the second one (confidence 1)." */
public static final String PARAMETER_SECOND_CLASS = "second_class";
public ThresholdCreator(OperatorDescription description) {
super(description);
}
public IOObject[] apply() throws OperatorException {
double threshold = getParameterAsDouble(PARAMETER_THRESHOLD);
String negativeClass = getParameterAsString(PARAMETER_FIRST_CLASS);
String positiveClass = getParameterAsString(PARAMETER_SECOND_CLASS);
return new IOObject[] { new Threshold(threshold, negativeClass, positiveClass) };
}
public Class<?>[] getInputClasses() {
return new Class[0];
}
public Class<?>[] getOutputClasses() {
return new Class[] { Threshold.class };
}
public List<ParameterType> getParameterTypes() {
List<ParameterType> list = super.getParameterTypes();
ParameterType type = new ParameterTypeDouble(PARAMETER_THRESHOLD, "The confidence threshold to determine if the prediction should be positive.", 0, 1.0d, 0.5d);
type.setExpert(false);
list.add(type);
list.add(new ParameterTypeString(PARAMETER_FIRST_CLASS, "The class which should be considered as the first one (confidence 0).", false));
list.add(new ParameterTypeString(PARAMETER_SECOND_CLASS, "The class which should be considered as the second one (confidence 1).", false));
return list;
}
}