Example usage for weka.classifiers RandomizableIteratedSingleClassifierEnhancer subclass-usage

Introduction

In this page you can find the example usage for weka.classifiers RandomizableIteratedSingleClassifierEnhancer subclass-usage.

Usage

From source file BaggingImprove.java

/**
 *
 * @author sartikahasibuan
 */
public class BaggingImprove extends RandomizableIteratedSingleClassifierEnhancer
        implements WeightedInstancesHandler, AdditionalMeasureProducer, TechnicalInformationHandler {

From source file com.tum.classifiertest.FastRfBagging.java

/**
 * Based on the "weka.classifiers.meta.Bagging" class, revision 1.39,
 * by Kirkby, Frank and Trigg, with modifications:
 * <ul>
 * <p/>
 * <li>Instead of Instances, produces DataCaches; consequently, FastRfBagging

From source file gyc.OverBoostM1.java

/**
 <!-- globalinfo-start -->
 * Class for boosting a nominal class classifier using the Adaboost M1 method. Only nominal class problems can be tackled. Often dramatically improves performance, but sometimes overfits.<br/>
 * <br/>
 * For more information, see<br/>
 * <br/>

From source file gyc.SMOTEBagging.java

/**
 <!-- globalinfo-start -->
 * Class for bagging a classifier to reduce variance. Can do classification and regression depending on the base learner. <br/>
 * <br/>
 * For more information, see<br/>
 * <br/>

From source file gyc.UnderOverBoostM1.java

/**
 <!-- globalinfo-start -->
 * Class for boosting a nominal class classifier using the Adaboost M1 method. Only nominal class problems can be tackled. Often dramatically improves performance, but sometimes overfits.<br/>
 * <br/>
 * For more information, see<br/>
 * <br/>

From source file hr.irb.fastRandomForest.FastRfBagging.java

/**
 * Based on the "weka.classifiers.meta.Bagging" class, revision 1.39,
 * by Kirkby, Frank and Trigg, with modifications:
 * <ul>
 * <p/>
 * <li>Instead of Instances, produces DataCaches; consequently, FastRfBagging