Example usage for weka.classifiers Classifier subclass-usage

Introduction

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

Usage

From source file myclassifier.MyC45.java

public class MyC45 extends Classifier {
    /** The node's successors. */
    private MyC45[] m_Successors;

    /** Attribute used for splitting. */
    private Attribute m_Attribute;

From source file myid3andc45classifier.Model.MyC45.java

/**
 *
 * @author ryanyonata
 */
public class MyC45 extends Classifier {

From source file myid3andc45classifier.Model.MyID3.java

/**
 *
 * @author ryanyonata
 */
public class MyID3 extends Classifier {

From source file net.sf.bddbddb.order.MyId3.java

/**
 * Class implementing an Id3 decision tree classifier. This version differs from
 * the weka one in that it supports missing attributes.
 * 
 * @author Eibe Frank (eibe@cs.waikato.ac.nz)
 * @author John Whaley

From source file neuralnetwork.NeuralNet.java

/**
 *
 * @author Harvey
 */
public class NeuralNet extends Classifier {
    private List<Double> mInput; // First layer inputs

From source file newdtl.NewID3.java

public class NewID3 extends Classifier {

    private final double DOUBLE_MISSING_VALUE = Double.NaN;

    /**
     * The node's children.

From source file newdtl.NewJ48.java

public class NewJ48 extends Classifier {

    private final double DOUBLE_MISSING_VALUE = Double.NaN;
    private final double DOUBLE_ERROR_MAXIMUM = 1e-6;

    /**

From source file org.if4071.myann.PerceptronTrainingRule.java

/**
 *
 * @author Fahmi
 */
public class PerceptronTrainingRule extends Classifier {
    /*ATTRIBUTE*/

From source file org.scripps.branch.classifier.ManualTree.java

/**
 * <!-- globalinfo-start --> Class for constructing a tree when the structure of
 * the tree has been completely determined elsewhere. <!-- globalinfo-end -->
 * 
 * <!-- options-start --> Valid options are:
 * <p/>

From source file Reader.KnnClassifier.java

/**
 *
 * @author Schuyler
 */
public class KnnClassifier extends Classifier implements Serializable {
    private Instances trainingData;