CVParameterSelection

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.SingleClassifierEnhancer
  - - weka.classifiers.RandomizableSingleClassifierEnhancer
    - - weka.classifiers.meta.CVParameterSelection

All Implemented Interfaces:: java.io.Serializable, java.lang.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: 15520 $
Author:: Len Trigg (trigg@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary
- Fields inherited from class weka.classifiers.AbstractClassifier
  BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT
- Fields inherited from interface weka.core.Drawable
  BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors
Constructor and Description

CVParameterSelection()

Constructors
Constructor and Description
`CVParameterSelection()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`addCVParameter(java.lang.String cvParam)` Adds a scheme parameter to the list of parameters to be set by cross-validation
`void`	`buildClassifier(Instances instances)` Generates the classifier.
`java.lang.String`	`CVParametersTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance instance)` Predicts the class distribution for the given test instance.
`java.lang.String[]`	`getBestClassifierOptions()` Returns (a copy of) the best options found for the classifier.
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`java.lang.String`	`getCVParameter(int index)` Gets the scheme paramter with the given index.
`java.lang.Object[]`	`getCVParameters()` Get method for CVParameters.
`int`	`getNumFolds()` Gets the number of folds for the cross-validation.
`java.lang.String[]`	`getOptions()` Gets the current settings of the Classifier.
`java.lang.String`	`getRevision()` Returns the revision string.
`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.
`java.lang.String`	`globalInfo()` Returns a string describing this classifier
`java.lang.String`	`graph()` Returns graph describing the classifier (if possible).
`int`	`graphType()` Returns the type of graph this classifier represents.
`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`	`numFoldsTipText()` Returns the tip text for this property
`void`	`setCVParameters(java.lang.Object[] params)` Set method for CVParameters.
`void`	`setNumFolds(int numFolds)` Sets the number of folds for the cross-validation.
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`java.lang.String`	`toString()` Returns description of the cross-validated classifier.
`java.lang.String`	`toSummaryString()` A concise description of the model.

Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer
getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, postExecution, preExecution, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - CVParameterSelection
```
public CVParameterSelection()
```
- Method Detail
  - globalInfo
```
public java.lang.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 java.util.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(java.lang.String[] options)
                throws java.lang.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:
    
    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 RandomizableSingleClassifierEnhancer
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - getBestClassifierOptions
```
public java.lang.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 Classifier
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class SingleClassifierEnhancer
    
    Returns:
    
    the capabilities of this classifier
    
    See Also:
    
    Capabilities
  - buildClassifier
```
public void buildClassifier(Instances instances)
                     throws java.lang.Exception
```
    Generates the classifier.
    
    Specified by:
    
    buildClassifier in interface Classifier
    
    Parameters:
    
    instances - set of instances serving as training data
    
    Throws:
    
    java.lang.Exception - if the classifier has not been generated successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance instance)
                                 throws java.lang.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:
    
    java.lang.Exception - if an error occurred during the prediction
  - addCVParameter
```
public void addCVParameter(java.lang.String cvParam)
                    throws java.lang.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:
    
    java.lang.Exception - if the parameter specifier is of the wrong format
  - getCVParameter
```
public java.lang.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 java.lang.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 java.lang.Object[] getCVParameters()
```
    Get method for CVParameters.
    
    Returns:
    
    the CVParameters
  - setCVParameters
```
public void setCVParameters(java.lang.Object[] params)
                     throws java.lang.Exception
```
    Set method for CVParameters.
    
    Parameters:
    
    params - the CVParameters to use
    
    Throws:
    
    java.lang.Exception - if the setting of the CVParameters fails
  - numFoldsTipText
```
public java.lang.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 java.lang.Exception
```
    Sets the number of folds for the cross-validation.
    
    Parameters:
    
    numFolds - the number of folds for the cross-validation
    
    Throws:
    
    java.lang.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 java.lang.String graph()
                       throws java.lang.Exception
```
    Returns graph describing the classifier (if possible).
    
    Specified by:
    
    graph in interface Drawable
    
    Returns:
    
    the graph of the classifier in dotty format
    
    Throws:
    
    java.lang.Exception - if the classifier cannot be graphed
  - toString
```
public java.lang.String toString()
```
    Returns description of the cross-validated classifier.
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    description of the cross-validated classifier as a string
  - toSummaryString
```
public java.lang.String toSummaryString()
```
    A concise description of the model.
    
    Specified by:
    
    toSummaryString in interface Summarizable
    
    Returns:
    
    a concise description of the model
  - getRevision
```
public java.lang.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(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - the options

Class CVParameterSelection

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

Fields inherited from interface weka.core.Drawable

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

CVParameterSelection

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

getBestClassifierOptions

getCapabilities

buildClassifier

distributionForInstance

addCVParameter

getCVParameter

CVParametersTipText

getCVParameters

setCVParameters

numFoldsTipText

getNumFolds

setNumFolds

graphType

graph

toString

toSummaryString

getRevision

main