Class RegressorToClassifier

JSAT/src/jsat/classifiers/RegressorToClassifier.java:24–109

This meta algorithm wraps a Regressor to perform binary classification. This is done my labeling class 0 data points as "-1" and class 1 points as "1". The sign of the outputs then determines the class. Not all regression algorithms will work well in this setting, and standard parameter valu

 * @author Edward Raff
 */
public class RegressorToClassifier implements BinaryScoreClassifier, Parameterized
{

	private static final long serialVersionUID = -2607433019826385335L;
	private Regressor regressor;

    /**
     * Creates a new Binary Classifier by using the given regressor 
     * @param regressor the regressor to wrap as a binary classifier 
     */
    public RegressorToClassifier(Regressor regressor)
    {
        this.regressor = regressor;
    }

    @Override
    public double getScore(DataPoint dp)
    {
        return regressor.regress(dp);
    }

    @Override
    public RegressorToClassifier clone()
    {
        return new RegressorToClassifier(regressor.clone());
    }

    @Override
    public CategoricalResults classify(DataPoint data)
    {
        CategoricalResults cr = new CategoricalResults(2);
        if(getScore(data) > 0)
            cr.setProb(1, 1.0);
        else
            cr.setProb(0, 1.0);
            
        return cr;
    }

    @Override
    public void trainC(ClassificationDataSet dataSet, ExecutorService threadPool)
    {
        RegressionDataSet rds = getRegressionDataSet(dataSet);
        regressor.train(rds, threadPool);
    }

    @Override
    public void trainC(ClassificationDataSet dataSet)
    {
        RegressionDataSet rds = getRegressionDataSet(dataSet);
        regressor.train(rds);
    }

    @Override
    public boolean supportsWeightedData()
    {
        return regressor.supportsWeightedData();
    }