/*
* EvaluateModel.java
* Copyright (C) 2007 University of Waikato, Hamilton, New Zealand
* @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
package tr.gov.ulakbim.jDenetX.tasks;
import tr.gov.ulakbim.jDenetX.classifiers.Classifier;
import tr.gov.ulakbim.jDenetX.core.ObjectRepository;
import tr.gov.ulakbim.jDenetX.evaluation.ClassificationPerformanceEvaluator;
import tr.gov.ulakbim.jDenetX.evaluation.LearningEvaluation;
import tr.gov.ulakbim.jDenetX.options.ClassOption;
import tr.gov.ulakbim.jDenetX.options.IntOption;
import tr.gov.ulakbim.jDenetX.streams.InstanceStream;
import weka.core.Instance;
public class EvaluateModel extends MainTask {
@Override
public String getPurposeString() {
return "Evaluates a static model on a stream.";
}
private static final long serialVersionUID = 1L;
public ClassOption modelOption = new ClassOption("model", 'm',
"Classifier to evaluate.", Classifier.class, "LearnModel");
public ClassOption streamOption = new ClassOption("stream", 's',
"Stream to evaluate on.", InstanceStream.class,
"generators.RandomTreeGenerator");
public ClassOption evaluatorOption = new ClassOption("evaluator", 'e',
"Classification performance evaluation method.",
ClassificationPerformanceEvaluator.class,
"BasicClassificationPerformanceEvaluator");
public IntOption maxInstancesOption = new IntOption("maxInstances", 'i',
"Maximum number of instances to test.", 1000000, 0,
Integer.MAX_VALUE);
public EvaluateModel() {
}
public EvaluateModel(Classifier model, InstanceStream stream,
ClassificationPerformanceEvaluator evaluator, int maxInstances) {
this.modelOption.setCurrentObject(model);
this.streamOption.setCurrentObject(stream);
this.evaluatorOption.setCurrentObject(evaluator);
this.maxInstancesOption.setValue(maxInstances);
}
public Class<?> getTaskResultType() {
return LearningEvaluation.class;
}
@Override
public Object doMainTask(TaskMonitor monitor, ObjectRepository repository) {
Classifier model = (Classifier) getPreparedClassOption(this.modelOption);
InstanceStream stream = (InstanceStream) getPreparedClassOption(this.streamOption);
ClassificationPerformanceEvaluator evaluator = (ClassificationPerformanceEvaluator) getPreparedClassOption(this.evaluatorOption);
int maxInstances = this.maxInstancesOption.getValue();
long instancesProcessed = 0;
monitor.setCurrentActivity("Evaluating model...", -1.0);
while (stream.hasMoreInstances()
&& ((maxInstances < 0) || (instancesProcessed < maxInstances))) {
Instance testInst = (Instance) stream.nextInstance().copy();
int trueClass = (int) testInst.classValue();
testInst.setClassMissing();
double[] prediction = model.getVotesForInstance(testInst);
evaluator.addClassificationAttempt(trueClass, prediction, testInst
.weight());
instancesProcessed++;
if (instancesProcessed % INSTANCES_BETWEEN_MONITOR_UPDATES == 0) {
if (monitor.taskShouldAbort()) {
return null;
}
long estimatedRemainingInstances = stream
.estimatedRemainingInstances();
if (maxInstances > 0) {
long maxRemaining = maxInstances - instancesProcessed;
if ((estimatedRemainingInstances < 0)
|| (maxRemaining < estimatedRemainingInstances)) {
estimatedRemainingInstances = maxRemaining;
}
}
monitor
.setCurrentActivityFractionComplete(estimatedRemainingInstances < 0 ? -1.0
: (double) instancesProcessed
/ (double) (instancesProcessed + estimatedRemainingInstances));
if (monitor.resultPreviewRequested()) {
monitor.setLatestResultPreview(new LearningEvaluation(
evaluator.getPerformanceMeasurements()));
}
}
}
return new LearningEvaluation(evaluator.getPerformanceMeasurements());
}
}