/*
* Copyright (C) 2013 Serdar
*
* 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 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package de.fub.maps.project.detector.model.inference.processhandler;
import de.fub.maps.project.detector.model.gpx.TrackSegment;
import de.fub.maps.project.detector.model.inference.AbstractInferenceModel;
import de.fub.maps.project.detector.model.inference.features.FeatureProcess;
import weka.classifiers.Evaluation;
import weka.core.Attribute;
import weka.core.DenseInstance;
import weka.core.Instance;
/**
*
* @author Serdar
*/
public abstract class EvaluationProcessHandler extends InferenceModelProcessHandler {
public EvaluationProcessHandler(AbstractInferenceModel inferenceModel) {
super(inferenceModel);
}
protected abstract void updateVisualRepresentation(Evaluation evaluation);
protected Instance getInstance(String className, TrackSegment dataset) {
Instance instance = new DenseInstance(getInferenceModel().getAttributes().size());
for (FeatureProcess feature : getInferenceModel().getFeatureList()) {
feature.setInput(dataset);
feature.run();
String featureName = feature.getName();
Attribute attribute = getInferenceModel().getAttributeMap().get(featureName);
Double result = feature.getResult();
instance.setValue(attribute, result);
}
instance.setValue(getInferenceModel().getAttributeMap().get(AbstractInferenceModel.CLASSES_ATTRIBUTE_NAME), className);
return instance;
}
}