/*
* 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.performance;
import java.util.List;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.IOObject;
import com.rapidminer.operator.InputDescription;
import com.rapidminer.operator.MissingIOObjectException;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.ValueDouble;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeCategory;
/**
* Returns a performance vector just counting the number of attributes currently
* used for the given example set.
*
* @author Ingo Mierswa
* @version $Id: AttributeCounter.java,v 1.8 2008/08/25 08:10:40 ingomierswa Exp $
*/
public class AttributeCounter extends Operator {
/** The parameter name for "Indicates if the fitness should for maximal or minimal number of features." */
public static final String PARAMETER_OPTIMIZATION_DIRECTION = "optimization_direction";
private double lastCount = Double.NaN;
public AttributeCounter(OperatorDescription description) {
super(description);
addValue(new ValueDouble("attributes", "The currently selected number of attributes.") {
public double getDoubleValue() {
return lastCount;
}
});
}
/**
* Creates a new performance vector if the given one is null. Adds a MDL
* criterion. If the criterion was already part of the performance vector
* before it will be overwritten.
*/
private PerformanceVector count(ExampleSet exampleSet, PerformanceVector performanceCriteria) throws OperatorException {
if (performanceCriteria == null)
performanceCriteria = new PerformanceVector();
MDLCriterion mdlCriterion = new MDLCriterion(getParameterAsInt(PARAMETER_OPTIMIZATION_DIRECTION));
mdlCriterion.startCounting(exampleSet, true);
this.lastCount = mdlCriterion.getAverage();
performanceCriteria.addCriterion(mdlCriterion);
return performanceCriteria;
}
public IOObject[] apply() throws OperatorException {
ExampleSet exampleSet = getInput(ExampleSet.class);
PerformanceVector inputPerformance = null;
try {
inputPerformance = getInput(PerformanceVector.class);
} catch (MissingIOObjectException e) {
// tries to use input performance if available
// no problem if none is given --> create new
}
PerformanceVector performance = count(exampleSet, inputPerformance);
return new IOObject[] { performance };
}
/** Shows a parameter keep_example_set with default value "false". */
public InputDescription getInputDescription(Class cls) {
if (ExampleSet.class.isAssignableFrom(cls)) {
return new InputDescription(cls, false, true);
} else {
return super.getInputDescription(cls);
}
}
public Class<?>[] getInputClasses() {
return new Class[] { ExampleSet.class };
}
public Class<?>[] getOutputClasses() {
return new Class[] { PerformanceVector.class };
}
public List<ParameterType> getParameterTypes() {
List<ParameterType> types = super.getParameterTypes();
types.add(new ParameterTypeCategory(PARAMETER_OPTIMIZATION_DIRECTION, "Indicates if the fitness should be maximal for the maximal or for the minimal number of features.", MDLCriterion.DIRECTIONS, MDLCriterion.MINIMIZATION));
return types;
}
}