weka.classifiers.meta

## Class RandomizableFilteredClassifier

- java.lang.Object
- - weka.classifiers.AbstractClassifier
  - - weka.classifiers.SingleClassifierEnhancer
    - - weka.classifiers.meta.FilteredClassifier
      - - weka.classifiers.meta.RandomizableFilteredClassifier

- All Implemented Interfaces:
    java.io.Serializable, java.lang.Cloneable, Classifier, IterativeClassifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, Drawable, OptionHandler, PartitionGenerator, Randomizable, RevisionHandler

      public class RandomizableFilteredClassifier
      extends FilteredClassifier
      implements Randomizable

  Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. Like the classifier, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.

  Valid options are:

       -F <filter specification>
        Full class name of filter to use, followed
        by filter options.
        eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"

       -D
        If set, classifier is run in debug mode and
        may output additional info to the console

       -W
        Full name of base classifier.
        (default: weka.classifiers.trees.J48)

       Options specific to classifier weka.classifiers.trees.J48:

       -U
        Use unpruned tree.

       -C <pruning confidence>
        Set confidence threshold for pruning.
        (default 0.25)

       -M <minimum number of instances>
        Set minimum number of instances per leaf.
        (default 2)

       -R
        Use reduced error pruning.

       -N <number of folds>
        Set number of folds for reduced error
        pruning. One fold is used as pruning set.
        (default 3)

       -B
        Use binary splits only.

       -S
        Don't perform subtree raising.

       -L
        Do not clean up after the tree has been built.

       -A
        Laplace smoothing for predicted probabilities.

       -Q <seed>
        Seed for random data shuffling (default 1).

  Version:
    $Revision: 9117 $
  Author:
    Eibe Frank
  See Also:
    Serialized Form

- - ### Field Summary

    - ### Fields inherited from interface weka.core.Drawable

      `BayesNet, Newick, NOT_DRAWABLE, TREE`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `RandomizableFilteredClassifier()` Default constructor.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `void` | `buildClassifier(Instances data)` Build the classifier on the filtered data.
    `java.lang.String[]` | `getOptions()` Gets the current settings of the classifier.
    `java.lang.String` | `getRevision()` Returns the revision string.
    `int` | `getSeed()` Gets the seed for the random number generations
    `java.lang.String` | `globalInfo()` Returns a string describing this classifier
    `java.util.Enumeration<Option>` | `listOptions()` Returns an enumeration describing the available options.
    `static void` | `main(java.lang.String[] argv)` Main method for testing this class.
    `java.lang.String` | `seedTipText()` Returns the tip text for this property
    `void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
    `void` | `setSeed(int seed)` Set the seed for random number generation.
    `java.lang.String` | `toString()` Output a representation of this classifier

    - ### Methods inherited from class weka.classifiers.meta.FilteredClassifier

      `batchSizeTipText, distributionForInstance, distributionsForInstances, done, filterTipText, generatePartition, getBatchSize, getCapabilities, getFilter, getMembershipValues, graph, graphType, initializeClassifier, next, numElements, setBatchSize, setFilter`

    - ### Methods inherited from class weka.classifiers.SingleClassifierEnhancer

      `classifierTipText, getClassifier, setClassifier`

    - ### Methods inherited from class weka.classifiers.AbstractClassifier

      `classifyInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, runClassifier, setDebug, setDoNotCheckCapabilities`

    - ### Methods inherited from class java.lang.Object

      `equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

    - ### Methods inherited from interface weka.classifiers.Classifier

      `classifyInstance`

- - ### Constructor Detail

    - #### RandomizableFilteredClassifier

          public RandomizableFilteredClassifier()

      Default constructor.

  - ### Method Detail

    - #### globalInfo

          public java.lang.String globalInfo()

      Returns a string describing this classifier
      Overrides:
        `globalInfo` in class `FilteredClassifier`
      Returns:
        a description of the classifier suitable for displaying in the explorer/experimenter gui

    - #### listOptions

          public java.util.Enumeration<Option> listOptions()

      Returns an enumeration describing the available options.
      Specified by:
        `listOptions` in interface `OptionHandler`
      Overrides:
        `listOptions` in class `FilteredClassifier`
      Returns:
        an enumeration of all the available options.

    - #### setOptions

          public void setOptions(java.lang.String[] options)
                          throws java.lang.Exception

      Parses a given list of options. Valid options are:

      -W classname
      Specify the full class name of the base learner.

      -I num
      Set the number of iterations (default 10).

      -S num
      Set the random number seed (default 1).

      Options after -- are passed to the designated classifier.

      Specified by:
        `setOptions` in interface `OptionHandler`
      Overrides:
        `setOptions` in class `FilteredClassifier`
      Parameters:
        `options` - the list of options as an array of strings
      Throws:
        `java.lang.Exception` - if an option is not supported

    - #### getOptions

          public java.lang.String[] getOptions()

      Gets the current settings of the classifier.
      Specified by:
        `getOptions` in interface `OptionHandler`
      Overrides:
        `getOptions` in class `FilteredClassifier`
      Returns:
        an array of strings suitable for passing to setOptions

    - #### seedTipText

          public java.lang.String seedTipText()

      Returns the tip text for this property
      Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

    - #### setSeed

          public void setSeed(int seed)

      Set the seed for random number generation.
      Specified by:
        `setSeed` in interface `Randomizable`
      Parameters:
        `seed` - the seed

    - #### getSeed

          public int getSeed()

      Gets the seed for the random number generations
      Specified by:
        `getSeed` in interface `Randomizable`
      Returns:
        the seed for the random number generation

    - #### buildClassifier

          public void buildClassifier(Instances data)
                               throws java.lang.Exception

      Build the classifier on the filtered data.
      Specified by:
        `buildClassifier` in interface `Classifier`
      Overrides:
        `buildClassifier` in class `FilteredClassifier`
      Parameters:
        `data` - the training data
      Throws:
        `java.lang.Exception` - if the classifier could not be built successfully

    - #### toString

          public java.lang.String toString()

      Output a representation of this classifier
      Overrides:
        `toString` in class `FilteredClassifier`
      Returns:
        a representation of this classifier

    - #### getRevision

          public java.lang.String getRevision()

      Returns the revision string.
      Specified by:
        `getRevision` in interface `RevisionHandler`
      Overrides:
        `getRevision` in class `FilteredClassifier`
      Returns:
        the revision

    - #### main

          public static void main(java.lang.String[] argv)

      Main method for testing this class.
      Parameters:
        `argv` - should contain the following arguments: -t training file [-T test file] [-c class index]