/*
* 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.features.weighting;
import java.util.LinkedList;
import java.util.List;
import weka.attributeSelection.ASEvaluation;
import weka.attributeSelection.AttributeEvaluator;
import weka.core.Instances;
import weka.core.OptionHandler;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformationHandler;
import weka.core.UnassignedClassException;
import com.rapidminer.example.Attribute;
import com.rapidminer.example.AttributeWeights;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.tools.WekaInstancesAdaptor;
import com.rapidminer.tools.WekaTools;
/**
* Performs the AttributeEvaluator of Weka with the same name to determine a
* sort of attribute relevance. These relevance values build an instance of
* AttributeWeights. Therefore, they can be used by other operators which make
* use of such weights, like weight based selection or search heuristics which
* use attribute weights to speed up the search. See the Weka javadoc for
* further operator and parameter descriptions.
*
* @author Ingo Mierswa
* @version $Id: GenericWekaAttributeWeighting.java,v 1.10 2006/04/05 09:42:01
* ingomierswa Exp $
*/
public class GenericWekaAttributeWeighting extends AbstractWeighting implements TechnicalInformationHandler {
public static final String[] WEKA_ATTRIBUTE_EVALUATORS = WekaTools.getWekaClasses(AttributeEvaluator.class);
/** The list with the weka parameters. */
private List<ParameterType> wekaParameters = new LinkedList<ParameterType>();
public GenericWekaAttributeWeighting(OperatorDescription description) {
super(description);
}
public AttributeWeights calculateWeights(ExampleSet exampleSet) throws OperatorException {
AttributeWeights weights = new AttributeWeights();
ASEvaluation evaluator = getWekaAttributeEvaluator(getOperatorClassName(), WekaTools.getWekaParametersFromTypes(this, wekaParameters));
log("Converting to Weka instances.");
Instances instances = WekaTools.toWekaInstances(exampleSet, "WeightingInstances", WekaInstancesAdaptor.WEIGHTING);
try {
log("Building Weka attribute evaluator.");
evaluator.buildEvaluator(instances);
//evaluator.buildEvaluator(instances);
} catch (UnassignedClassException e) {
throw new UserError(this, e, 105, new Object[] { getOperatorClassName(), e });
} catch (ArrayIndexOutOfBoundsException e) {
throw new UserError(this, e, 105, new Object[] { getOperatorClassName(), e });
} catch (Exception e) {
throw new UserError(this, e, 905, new Object[] { getOperatorClassName(), e });
}
int index = 0;
if (evaluator instanceof AttributeEvaluator) {
AttributeEvaluator singleEvaluator = (AttributeEvaluator)evaluator;
for (Attribute attribute : exampleSet.getAttributes()) {
try {
double result = singleEvaluator.evaluateAttribute(index++);
weights.setWeight(attribute.getName(), result);
} catch (Exception e) {
logWarning("Cannot evaluate attribute '" + attribute.getName() + "', use unknown weight.");
}
}
} else {
logWarning("Cannot evaluate attributes, use unknown weights.");
}
return weights;
}
/**
* Returns the Weka attribute evaluator based on the subtype of this
* operator.
*/
private ASEvaluation getWekaAttributeEvaluator(String prefixName, String[] parameters) throws OperatorException {
String actualName = prefixName.substring(WekaTools.WEKA_OPERATOR_PREFIX.length());
String evaluatorName = null;
for (int i = 0; i < WEKA_ATTRIBUTE_EVALUATORS.length; i++) {
if (WEKA_ATTRIBUTE_EVALUATORS[i].endsWith(actualName)) {
evaluatorName = WEKA_ATTRIBUTE_EVALUATORS[i];
break;
}
}
ASEvaluation evaluator = null;
try {
evaluator = (ASEvaluation) ASEvaluation.forName(evaluatorName, parameters);
} catch (Exception e) {
throw new UserError(this, e, 904, new Object[] { evaluatorName, e });
}
return evaluator;
}
public TechnicalInformation getTechnicalInformation() {
try {
ASEvaluation evaluator = getWekaAttributeEvaluator(getOperatorClassName(), null);
if (evaluator instanceof TechnicalInformationHandler)
return ((TechnicalInformationHandler)evaluator).getTechnicalInformation();
else
return null;
} catch (OperatorException e) {
return null;
}
}
public List<ParameterType> getParameterTypes() {
List<ParameterType> types = super.getParameterTypes();
ASEvaluation evaluator = null;
try {
// parameters must be null, not an empty String[0] array!
evaluator = getWekaAttributeEvaluator(getOperatorClassName(), null);
} catch (OperatorException e) {
throw new RuntimeException("Cannot instantiate Weka attribute evaluator " + getOperatorClassName() + ": " + e.getMessage());
}
wekaParameters = new LinkedList<ParameterType>();
if ((evaluator != null) && (evaluator instanceof OptionHandler)) {
WekaTools.addParameterTypes((OptionHandler) evaluator, types, wekaParameters, false, null);
}
return types;
}
}