/* * 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; } }