Example usage for weka.core OptionHandler interface-usage

Introduction

In this page you can find the example usage for weka.core OptionHandler interface-usage.

Usage

From source file PrincipalComponents.java

/**
 * <!-- globalinfo-start --> Performs a principal components analysis and
 * transformation of the data. Use in conjunction with a Ranker search.
 * Dimensionality reduction is accomplished by choosing enough eigenvectors to
 * account for some percentage of the variance in the original data---default
 * 0.95 (95%). Attribute noise can be filtered by transforming to the PC space,

From source file TextDirectoryLoader.java

/**
 <!-- globalinfo-start -->
 * Loads all text files in a directory and uses the subdirectory names as class labels. The content of the text files will be stored in a String attribute, the filename can be stored as well.
 * <p/>
 <!-- globalinfo-end -->
 *

From source file ArrayLoader.java

/**
 <!-- globalinfo-start -->
 * Reads a source that is in comma separated or tab separated format. Assumes that the first row in the file determines the number of and names of the attributes.
 * <p/>
 <!-- globalinfo-end -->
 *

From source file REPTree.java

/**
 <!-- globalinfo-start -->
 * Fast decision tree learner. Builds a decision/regression tree using information gain/variance and prunes it using reduced-error pruning (with backfitting).  Only sorts values for numeric attributes once. Missing values are dealt with by splitting the corresponding instances into pieces (i.e. as in C4.5).
 * <p/>
 <!-- globalinfo-end -->
 *

From source file REPRandomTree.java

/**
 <!-- globalinfo-start -->
 * Fast decision tree learner. Builds a decision/regression tree using information gain/variance and prunes it using reduced-error pruning (with backfitting).  Only sorts values for numeric attributes once. Missing values are dealt with by splitting the corresponding instances into pieces (i.e. as in C4.5).
 * <p/>
 <!-- globalinfo-end -->
 *

From source file CJWeka.java

public class CJWeka extends AbstractClassifier implements CJProxy, OptionHandler, WeightedInstancesHandler {

    /** for serialization */
    private static final long serialVersionUID = -4393145704384476775L;

    private static Instances ii;

From source file MultiClassClassifier.java

/**
 <!-- globalinfo-start -->
 * A metaclassifier for handling multi-class datasets with 2-class classifiers. This classifier is also capable of applying error correcting output codes for increased accuracy.
 * <p/>
 <!-- globalinfo-end -->
 *

From source file GainRatioAttributeEval1.java

/** 
 <!-- globalinfo-start -->
 * GainRatioAttributeEval :<br/>
 * <br/>
 * Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.<br/>
 * <br/>

From source file WrapperSubset.java

/**
 * <!-- globalinfo-start --> WrapperSubsetEval:<br/>
 * <br/>
 * Evaluates attribute sets by using a learning scheme. Cross validation is used
 * to estimate the accuracy of the learning scheme for a set of attributes.<br/>
 * <br/>

From source file SpectralClusterer.java

/**
 * <p>
 * Spectral clusterer class. For more information see:
 * <ul>
 * <li>Shi, J., and J. Malik (1997) "Normalized Cuts and Image Segmentation",
 * in Proc. of IEEE Conf. on Comp. Vision and Pattern Recognition, Puerto Rico</li>