Package weka.classifiers.meta

Class CVParameterSelection

java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.RandomizableSingleClassifierEnhancer
weka.classifiers.meta.CVParameterSelection
All Implemented Interfaces:
Serializable, Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, Drawable, OptionHandler, Randomizable, RevisionHandler, Summarizable, TechnicalInformationHandler
public class CVParameterSelection extends RandomizableSingleClassifierEnhancer implements Drawable, Summarizable, TechnicalInformationHandler
Class for performing parameter selection by cross-validation for any classifier.

For more information, see:

R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.

BibTeX: 

 @phdthesis{Kohavi1995,
    address = {Department of Computer Science, Stanford University},
    author = {R. Kohavi},
    school = {Stanford University},
    title = {Wrappers for Performance Enhancement and Oblivious Decision Graphs},
    year = {1995}
 }

Valid options are: 

 -X <number of folds>
  Number of folds used for cross validation (default 10).
 -P <classifier parameter>
  Classifier parameter options.
  eg: "N 1 5 10" Sets an optimisation parameter for the
  classifier with name -N, with lower bound 1, upper bound
  5, and 10 optimisation steps. The upper bound may be the
  character 'A' or 'I' to substitute the number of
  attributes or instances in the training data,
  respectively. This parameter may be supplied more than
  once to optimise over several classifier options
  simultaneously.
 -S <num>
  Random number seed.
  (default 1)
 -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.rules.ZeroR)
 
 Options specific to classifier weka.classifiers.rules.ZeroR:
 
 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
Options after -- are passed to the designated sub-classifier.

Version:
$Revision: 15519 $
Author:
Len Trigg (trigg@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • CVParameterSelection

      public CVParameterSelection()

  • Method Details

    • globalInfo

      public String globalInfo()
      Returns a string describing this classifier
      Returns:
      a description of the classifier suitable for displaying in the explorer/experimenter gui

    • getTechnicalInformation

      public TechnicalInformation getTechnicalInformation()
      Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
      Specified by:
      getTechnicalInformation in interface TechnicalInformationHandler
      Returns:
      the technical information about this class

    • listOptions

      public Enumeration<Option> listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class RandomizableSingleClassifierEnhancer
      Returns:
      an enumeration of all the available options.

    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options.

      Valid options are: 

       -X <number of folds>
  Number of folds used for cross validation (default 10).
       -P <classifier parameter>
  Classifier parameter options.
  eg: "N 1 5 10" Sets an optimisation parameter for the
  classifier with name -N, with lower bound 1, upper bound
  5, and 10 optimisation steps. The upper bound may be the
  character 'A' or 'I' to substitute the number of
  attributes or instances in the training data,
  respectively. This parameter may be supplied more than
  once to optimise over several classifier options
  simultaneously.
       -S <num>
  Random number seed.
  (default 1)
       -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.rules.ZeroR)
       
 Options specific to classifier weka.classifiers.rules.ZeroR:
 
       -D
  If set, classifier is run in debug mode and
  may output additional info to the console
      Options after -- are passed to the designated sub-classifier.

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

    • getOptions

      public String[] getOptions()
      Gets the current settings of the Classifier.
      Specified by:
      getOptions in interface OptionHandler
      Overrides:
      getOptions in class RandomizableSingleClassifierEnhancer
      Returns:
      an array of strings suitable for passing to setOptions

    • getBestClassifierOptions

      public String[] getBestClassifierOptions()
      Returns (a copy of) the best options found for the classifier.
      Returns:
      the best options

    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      Specified by:
      getCapabilities in interface CapabilitiesHandler
      Specified by:
      getCapabilities in interface Classifier
      Overrides:
      getCapabilities in class SingleClassifierEnhancer
      Returns:
      the capabilities of this classifier
      See Also:

    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Generates the classifier.
      Specified by:
      buildClassifier in interface Classifier
      Parameters:
      instances - set of instances serving as training data
      Throws:
      Exception - if the classifier has not been generated successfully

    • distributionForInstance

      public double[] distributionForInstance(Instance instance) throws Exception
      Predicts the class distribution for the given test instance.
      Specified by:
      distributionForInstance in interface Classifier
      Overrides:
      distributionForInstance in class AbstractClassifier
      Parameters:
      instance - the instance to be classified
      Returns:
      the predicted class value
      Throws:
      Exception - if an error occurred during the prediction

    • addCVParameter

      public void addCVParameter(String cvParam) throws Exception
      Adds a scheme parameter to the list of parameters to be set by cross-validation
      Parameters:
      cvParam - the string representation of a scheme parameter. The format is:
      param_char lower_bound upper_bound number_of_steps
      eg to search a parameter -P from 1 to 10 by increments of 1:
      P 1 10 11
      Throws:
      Exception - if the parameter specifier is of the wrong format

    • getCVParameter

      public String getCVParameter(int index)
      Gets the scheme paramter with the given index.
      Parameters:
      index - the index for the parameter
      Returns:
      the scheme parameter

    • CVParametersTipText

      public String CVParametersTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getCVParameters

      public Object[] getCVParameters()
      Get method for CVParameters.
      Returns:
      the CVParameters

    • setCVParameters

      public void setCVParameters(Object[] params) throws Exception
      Set method for CVParameters.
      Parameters:
      params - the CVParameters to use
      Throws:
      Exception - if the setting of the CVParameters fails

    • numFoldsTipText

      public String numFoldsTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getNumFolds

      public int getNumFolds()
      Gets the number of folds for the cross-validation.
      Returns:
      the number of folds for the cross-validation

    • setNumFolds

      public void setNumFolds(int numFolds) throws Exception
      Sets the number of folds for the cross-validation.
      Parameters:
      numFolds - the number of folds for the cross-validation
      Throws:
      Exception - if parameter illegal

    • graphType

      public int graphType()
      Returns the type of graph this classifier represents.
      Specified by:
      graphType in interface Drawable
      Returns:
      the type of graph this classifier represents

    • graph

      public String graph() throws Exception
      Returns graph describing the classifier (if possible).
      Specified by:
      graph in interface Drawable
      Returns:
      the graph of the classifier in dotty format
      Throws:
      Exception - if the classifier cannot be graphed

    • toString

      public String toString()
      Returns description of the cross-validated classifier.
      Overrides:
      toString in class Object
      Returns:
      description of the cross-validated classifier as a string

    • toSummaryString

      public String toSummaryString()
      A concise description of the model.
      Specified by:
      toSummaryString in interface Summarizable
      Returns:
      a concise description of the model

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Overrides:
      getRevision in class AbstractClassifier
      Returns:
      the revision

    • main

      public static void main(String[] argv)
      Main method for testing this class.
      Parameters:
      argv - the options