Example usage for weka.classifiers.meta FilteredClassifier setFilter

Introduction

In this page you can find the example usage for weka.classifiers.meta FilteredClassifier setFilter.

Prototype

public void setFilter(Filter filter) 

Source Link

Document

Sets the filter

Usage

From source file:org.vimarsha.classifier.impl.FunctionWiseClassifier.java

License:Open Source License

/**
 * Classifies function wise test instances in the associated with the names labels mentioned in the arraylist passed as the argument.
 *
 * @param list - labels of instances contained in the test set that need to be classified.
 * @return TreeMap containing the instance labels and the associated classification results.
 * @throws ClassificationFailedException
 *//*from   ww  w .  j  a v  a  2s  .  c o  m*/
@Override
public LinkedHashMap<String, String> classify(LinkedList<String> list) throws ClassificationFailedException {
    output = new LinkedHashMap<String, String>();
    J48 j48 = new J48();
    Remove rm = new Remove();
    rm.setAttributeIndices("1");
    FilteredClassifier fc = new FilteredClassifier();
    fc.setFilter(rm);
    fc.setClassifier(j48);
    try {
        fc.buildClassifier(trainSet);
        for (int i = 0; i < testSet.numInstances(); i++) {
            double pred = fc.classifyInstance(testSet.instance(i));
            if (list.isEmpty()) {
                output.put(String.valueOf(i + 1), testSet.classAttribute().value((int) pred));
            } else {
                output.put(list.get(i), testSet.classAttribute().value((int) pred));
            }
        }
    } catch (Exception ex) {
        throw new ClassificationFailedException();
    }
    return output;
}

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From source file:org.vimarsha.classifier.impl.TimeslicedClassifier.java

License:Open Source License

/**
 * Classifies Timesliced test data instances.
 *
 * @return Resulting linked list with timelsiced classification results.
 * @throws ClassificationFailedException
 *///  w w w .j  a  v a2  s  .  c  o  m
@Override
public Object classify() throws ClassificationFailedException {
    output = new LinkedList<String>();
    J48 j48 = new J48();
    Remove rm = new Remove();
    rm.setAttributeIndices("1");
    FilteredClassifier fc = new FilteredClassifier();
    fc.setFilter(rm);
    fc.setClassifier(j48);
    try {
        fc.buildClassifier(trainSet);

        for (int i = 0; i < testSet.numInstances(); i++) {
            //System.out.println(testSet.instance(i));
            double pred = fc.classifyInstance(testSet.instance(i));
            output.add(testSet.classAttribute().value((int) pred));
        }
    } catch (Exception ex) {
        System.out.println(ex.toString());
        throw new ClassificationFailedException();
    }
    return output;
}

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From source file:org.vimarsha.classifier.impl.WholeProgramClassifier.java

License:Open Source License

/**
 * Classifies whole program test instances,
 *
 * @return String containing the classification result of the evaluated program's dataset.
 * @throws ClassificationFailedException
 */// w  w w .  ja  v a2  s  .  c om
@Override
public Object classify() throws ClassificationFailedException {
    J48 j48 = new J48();
    Remove rm = new Remove();
    String output = null;
    rm.setAttributeIndices("1");
    FilteredClassifier fc = new FilteredClassifier();
    fc.setFilter(rm);
    fc.setClassifier(j48);
    try {
        fc.buildClassifier(trainSet);
        this.treeModel = j48.toString();
        double pred = fc.classifyInstance(testSet.instance(0));
        output = testSet.classAttribute().value((int) pred);
        classificationResult = output;
    } catch (Exception ex) {
        throw new ClassificationFailedException();
    }
    return output;
}

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From source file:pl.nask.hsn2.service.analysis.JSWekaAnalyzer.java

License:Open Source License

private void createClassifier(String classifierName) {
    try {//w  w  w.j ava 2  s  .  c  o  m
        Classifier classifier = (Classifier) Class.forName(classifierName).newInstance();
        FilteredClassifier filteredClassifier = new FilteredClassifier();
        filteredClassifier.setClassifier(classifier);
        filteredClassifier.setFilter(new StringToWordVector());
        filteredClassifier.buildClassifier(trainingSet);
        fc = filteredClassifier;
    } catch (Exception e) {
        LOGGER.error(e.getMessage(), e);
    }
}

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From source file:prismcrossvalidation.Classifier.java

static public String crossValidationPRISM_DISCRET() throws FileNotFoundException, IOException, Exception {
    String prismResult = "";
    String source = MainWindow.pathChooseField.getText();
    Instances data = DataLoad.loadData(source.replace("\\", "/"));

    data.setClassIndex(data.numAttributes() - 1);

    Discretize filter = new Discretize();
    Prism rules = new Prism();

    FilteredClassifier fClassifier = new FilteredClassifier();
    fClassifier.setFilter(filter); //Ustawienie aktualnego filtra
    fClassifier.setClassifier(rules); //Ustawienie aktualnego klasyfikatora

    Evaluation eval = new MyEvaluation(data);
    eval.crossValidateModel(fClassifier, data, fold, new Random(1)); //CV dla 10 foldow

    System.out.println("amount of folds: " + fold);
    MainWindow.logArea.append("Amount of folds: " + fold);

    System.out.println(eval.toSummaryString("Wyniki:", false));
    MainWindow.logArea.append(eval.toSummaryString("Wyniki:", false));

    return prismResult = eval.toSummaryString("Wyniki:", false);
}

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