/**
* Copyright (C) 2001-2017 by RapidMiner and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapidminer.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.visualization;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.Model;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.operator.learner.PredictionModel;
import com.rapidminer.operator.ports.InputPort;
import com.rapidminer.operator.ports.OutputPort;
import com.rapidminer.operator.ports.metadata.ExampleSetPrecondition;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.math.LiftDataGenerator;
import java.util.List;
/**
* This operator creates a Lift chart for the given example set and model. The model will be applied
* on the example set and a lift chart will be produced afterwards.
*
* Please note that a predicted label of the given example set will be removed during the
* application of this operator.
*
* @author Ingo Mierswa
*/
public class LiftChartGenerator extends Operator {
private InputPort exampleSetInput = getInputPorts().createPort("example set");
private InputPort modelInput = getInputPorts().createPort("model", Model.class);
private OutputPort exampleSetOutput = getOutputPorts().createPort("example set");
private OutputPort modelOutput = getOutputPorts().createPort("model");
public LiftChartGenerator(OperatorDescription description) {
super(description);
exampleSetInput
.addPrecondition(new ExampleSetPrecondition(exampleSetInput, Attributes.LABEL_NAME, Ontology.NOMINAL));
getTransformer().addPassThroughRule(exampleSetInput, exampleSetOutput);
getTransformer().addPassThroughRule(modelInput, modelOutput);
}
@Override
public void doWork() throws OperatorException {
ExampleSet exampleSet = exampleSetInput.getData(ExampleSet.class);
Model model = modelInput.getData(Model.class);
if (exampleSet.getAttributes().getLabel() == null) {
throw new UserError(this, 105);
}
if (!exampleSet.getAttributes().getLabel().isNominal()) {
throw new UserError(this, 101, "Lift Charts", exampleSet.getAttributes().getLabel());
}
if (exampleSet.getAttributes().getLabel().getMapping().getValues().size() != 2) {
throw new UserError(this, 114, "Lift Charts", exampleSet.getAttributes().getLabel());
}
ExampleSet workingSet = (ExampleSet) exampleSet.clone();
if (workingSet.getAttributes().getPredictedLabel() != null) {
PredictionModel.removePredictedLabel(workingSet);
}
workingSet = model.apply(workingSet);
if (workingSet.getAttributes().getPredictedLabel() == null) {
throw new UserError(this, 107);
}
LiftDataGenerator liftDataGenerator = new LiftDataGenerator();
List<double[]> liftPoints = liftDataGenerator.createLiftDataList(workingSet);
liftDataGenerator.createLiftChartPlot(liftPoints);
PredictionModel.removePredictedLabel(workingSet);
exampleSetOutput.deliver(exampleSet);
modelOutput.deliver(model);
}
}