Class OneVSAll

JSAT/src/jsat/classifiers/OneVSAll.java:29–232

This classifier turns any classifier, specifically binary classifiers, into multi-class classifiers. For a problem with k target classes, OneVsALl will create k different classifiers. Each one is a reducing of one class against all other classes. Then all k classifiers's results

 * @author Edward Raff
 */
public class OneVSAll implements Classifier, Parameterized
{

    private static final long serialVersionUID = -326668337438092217L;
    private Classifier[] oneVsAlls;
    @ParameterHolder
    private Classifier baseClassifier;
    private CategoricalData predicting;
    private boolean concurrentTraining;
    private boolean useScoreIfAvailable = true;
    
    /**
     * Creates a new One VS All classifier. 
     * 
     * @param baseClassifier the base classifier to replicate  
     * @see #setConcurrentTraining(boolean) 
     */
    public OneVSAll(Classifier baseClassifier)
    {
        this(baseClassifier, true);
    }
    
    /**
     * Creates a new One VS All classifier. 
     * 
     * @param baseClassifier the base classifier to replicate
     * @param concurrentTraining controls whether or not classifiers are trained 
     * simultaneously or using sequentially using their 
     * {@link Classifier#trainC(jsat.classifiers.ClassificationDataSet, java.util.concurrent.ExecutorService) } method.  
     * @see #setConcurrentTraining(boolean) 
     */
    public OneVSAll(Classifier baseClassifier, boolean concurrentTraining)
    {
        this.baseClassifier = baseClassifier;
        this.concurrentTraining = concurrentTraining;
    }

    /**
     * Controls what method of parallel training to use when 
     * {@link #trainC(jsat.classifiers.ClassificationDataSet, java.util.concurrent.ExecutorService) } 
     * is called. If set to true, each of the <i>k</i> classifiers will be trained in parallel, using
     * their serial algorithms. If set to false, the <i>k</i> classifiers will be trained sequentially, 
     * calling the {@link Classifier#trainC(jsat.classifiers.ClassificationDataSet, java.util.concurrent.ExecutorService) }
     * for each classifier. <br>
     * <br>
     * This should be set to true for classifiers that do not support parallel training.<br>
     * Setting this to true also uses <i>k</i> times the memory, since each classifier is being created and trained at the same time. 
     * @param concurrentTraining whether or not to train the classifiers in parallel 
     */
    public void setConcurrentTraining(boolean concurrentTraining)
    {
        this.concurrentTraining = concurrentTraining;
    }
    
    
    @Override
    public CategoricalResults classify(DataPoint data)
    {