org.conqat.engine.commons.machine_learning.DataSetCreator.java Source code

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Here is the source code for org.conqat.engine.commons.machine_learning.DataSetCreator.java

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/*-------------------------------------------------------------------------+
|                                                                          |
| Copyright 2005-2011 the ConQAT Project                                   |
|                                                                          |
| Licensed under the Apache License, Version 2.0 (the "License");          |
| you may not use this file except in compliance with the License.         |
| You may obtain a copy of the License at                                  |
|                                                                          |
|    http://www.apache.org/licenses/LICENSE-2.0                            |
|                                                                          |
| Unless required by applicable law or agreed to in writing, software      |
| distributed under the License is distributed on an "AS IS" BASIS,        |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and      |
| limitations under the License.                                           |
+-------------------------------------------------------------------------*/
package org.conqat.engine.commons.machine_learning;

import org.conqat.lib.commons.assertion.CCSMAssert;
import org.conqat.lib.commons.collections.PairList;

import weka.core.Instance;
import weka.core.Instances;

/**
 * Class to create a data set for the weka library. T represents the class of
 * the objects in the data set, LABEL represents the label that can be assigned
 * to the classification objects by the classifier.
 * 
 * @author $Author: hummelb $
 * @version $Rev: 44457 $
 * @ConQAT.Rating GREEN Hash: EF070F7A75FD1939978A405921CB45DC
 */
public class DataSetCreator<T, LABEL extends Enum<LABEL>> {

    /** The training data set. */
    private Instances trainingDataSet;

    /**
     * Helper class to create a weka instance for a given classification object.
     */
    private final InstanceCreatorBase<T, LABEL> instanceCreator;

    /** List of classification objects and their labels as training data points. */
    private final PairList<T, LABEL> trainingDataPoints = new PairList<T, LABEL>();

    /** Constructor. */
    public DataSetCreator(InstanceCreatorBase<T, LABEL> instanceCreator) {
        this.instanceCreator = instanceCreator;

    }

    /** Constructor with a given dataset (e.g. possibly loaded from file) */
    public DataSetCreator(InstanceCreatorBase<T, LABEL> instanceCreator, Instances dataset) {
        this.instanceCreator = instanceCreator;

        this.trainingDataSet = dataset;
        dataset.setClassIndex(instanceCreator.getNumberOfFeatures());
    }

    /**
     * Creates a weka instance for the given classification object and adds it
     * to the training data set.
     * 
     * @param label
     *            The label of the classification object required for learning.
     * 
     */
    public void addData(T classificationObject, LABEL label) {
        CCSMAssert.isTrue(trainingDataSet == null, "TrainingDataSet not null when adding a data point");
        trainingDataPoints.add(classificationObject, label);
    }

    /**
     * Creates a weka instance for the given object. This method is used for an
     * object without label to be classified after learning. It creates an
     * instance with a default label.
     * 
     * @return The weka instance with a default label.
     */
    public Instance createWekaUnlabeledInstance(T object) {
        return createInstance(object, instanceCreator.getDefaultLabel(), createInstances(1));
    }

    /** Returns the data set. */
    public Instances getDataSet() {
        if (trainingDataSet == null) {
            trainingDataSet = createInstances(trainingDataPoints.size());

            for (int i = 0; i < trainingDataPoints.size(); i++) {
                createInstance(trainingDataPoints.getFirst(i), trainingDataPoints.getSecond(i), trainingDataSet);
            }
        }

        return trainingDataSet;
    }

    /**
     * Creates a weka instance for the given classification object and the given
     * label and adds it to the given data set.
     */
    private Instance createInstance(T classificationObject, LABEL label, Instances dataSet) {
        Instance instance = instanceCreator.createWekaInstance(classificationObject, label);
        dataSet.add(instance);
        instance.setDataset(dataSet);
        return instance;
    }

    /** Creates an instance set of the given size. */
    private Instances createInstances(int size) {
        Instances instances = new Instances("Rel", instanceCreator.getAttributes(), size);
        instances.setClassIndex(instanceCreator.getNumberOfFeatures());
        return instances;
    }

    /** Returns the instance creator. */
    public InstanceCreatorBase<T, LABEL> getInstanceCreator() {
        return instanceCreator;
    }
}