Example usage for weka.classifiers.meta FilteredClassifier setDoNotCheckForModifiedClassAttribute

Introduction

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

Prototype

public void setDoNotCheckForModifiedClassAttribute(boolean flag) 

Source Link

Document

Use this method to determine whether classifier checks whether class attribute has been modified by filter.

Usage

From source file:com.github.fracpete.multisearch.optimize.PLSFilterAndLinearRegression.java

License:Open Source License

/**
 * The first parameter must be dataset,/*from  w w  w .j av  a2 s.  c  o m*/
 * the (optional) second the class index (1-based, 'first' and 'last'
 * also supported).
 *
 * @param args   the commandline options
 * @throws Exception   if optimization fails for some reason
 */
public static void main(String[] args) throws Exception {
    if (args.length == 0) {
        System.err.println("\nUsage: PLSFilterAndLinearRegression <dataset> [classindex]\n");
        System.exit(1);
    }

    // load data
    Instances data = ExampleHelper.loadData(args[0], (args.length > 1) ? args[1] : null);

    // configure classifier we want to optimize
    PLSFilter pls = new PLSFilter();
    LinearRegression lr = new LinearRegression();
    FilteredClassifier fc = new FilteredClassifier();
    fc.setClassifier(lr);
    fc.setFilter(pls);
    // required for Weka > 3.7.13
    fc.setDoNotCheckForModifiedClassAttribute(true);

    // configure multisearch
    // 1. number of components
    ListParameter numComp = new ListParameter();
    numComp.setProperty("filter.numComponents");
    numComp.setList("2 5 7");
    // 2. ridge
    MathParameter ridge = new MathParameter();
    ridge.setProperty("classifier.ridge");
    ridge.setBase(10);
    ridge.setMin(-5);
    ridge.setMax(1);
    ridge.setStep(1);
    ridge.setExpression("pow(BASE,I)");
    // assemble everything
    MultiSearch multi = new MultiSearch();
    multi.setClassifier(fc);
    multi.setSearchParameters(new AbstractParameter[] { numComp, ridge });
    SelectedTag tag = new SelectedTag(DefaultEvaluationMetrics.EVALUATION_RMSE,
            new DefaultEvaluationMetrics().getTags());
    multi.setEvaluation(tag);

    // output configuration
    System.out.println("\nMultiSearch commandline:\n" + Utils.toCommandLine(multi));

    // optimize
    System.out.println("\nOptimizing...\n");
    multi.buildClassifier(data);
    System.out.println("Best setup:\n" + Utils.toCommandLine(multi.getBestClassifier()));
    System.out.println("Best parameters: " + multi.getGenerator().evaluate(multi.getBestValues()));
}

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From source file:com.github.fracpete.multisearch.setupgenerator.PLSFilterAndLinearRegression.java

License:Open Source License

/**
 * Outputs the commandlines./*from w  w w  .  j  av a2s .c o  m*/
 *
 * @param args   the commandline options
 * @throws Exception   if setup generator fails for some reason
 */
public static void main(String[] args) throws Exception {
    // configure classifier we want to generate setups for
    PLSFilter pls = new PLSFilter();
    LinearRegression lr = new LinearRegression();
    FilteredClassifier fc = new FilteredClassifier();
    fc.setClassifier(lr);
    fc.setFilter(pls);
    // required for Weka > 3.7.13
    fc.setDoNotCheckForModifiedClassAttribute(true);

    // configure generator
    // 1. number of components
    ListParameter numComp = new ListParameter();
    numComp.setProperty("filter.numComponents");
    numComp.setList("2 5 7");
    // 2. ridge
    MathParameter ridge = new MathParameter();
    ridge.setProperty("classifier.ridge");
    ridge.setBase(10);
    ridge.setMin(-5);
    ridge.setMax(1);
    ridge.setStep(1);
    ridge.setExpression("pow(BASE,I)");
    // assemble everything
    SetupGenerator generator = new SetupGenerator();
    generator.setBaseObject(fc);
    generator.setParameters(new AbstractParameter[] { numComp, ridge });

    // output configuration
    System.out.println("\nSetupgenerator commandline:\n" + Utils.toCommandLine(generator));

    // output commandlines
    System.out.println("\nCommandlines:\n");
    Enumeration<Serializable> enm = generator.setups();
    while (enm.hasMoreElements())
        System.out.println(Utils.toCommandLine(enm.nextElement()));
}

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