weka.experiment

Class ClassifierSplitEvaluator

java.lang.Object

weka.experiment.ClassifierSplitEvaluator

All Implemented Interfaces:

java.io.Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, SplitEvaluator

Direct Known Subclasses:

CostSensitiveClassifierSplitEvaluator

public class ClassifierSplitEvaluator
extends java.lang.Object
implements SplitEvaluator, OptionHandler, AdditionalMeasureProducer, RevisionHandler

A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.

Valid options are:

 -W <class name>
  The full class name of the classifier.
  eg: weka.classifiers.bayes.NaiveBayes
 

 -C <index>
  The index of the class for which IR statistics
  are to be output. (default 1)
 

 -I <index>
  The index of an attribute to output in the
  results. This attribute should identify an
  instance in order to know which instances are
  in the test set of a cross validation. if 0
  no output (default 0).
 

 -P
  Add target and prediction columns to the result
  for each fold.
 

 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
 

All options after -- will be passed to the classifier.

Version:

$Revision: 11198 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ClassifierSplitEvaluator() No args constructor.

Method Summary

Modifier and Type	Method and Description
java.lang.String	classifierTipText() Returns the tip text for this property
java.util.Enumeration	enumerateMeasures() Returns an enumeration of any additional measure names that might be in the classifier
int	getAttributeID() Get the index of Attibute Identifying the instances
int	getClassForIRStatistics() Get the value of ClassForIRStatistics.
Classifier	getClassifier() Get the value of Classifier.
java.lang.Object[]	getKey() Gets the key describing the current SplitEvaluator.
java.lang.String[]	getKeyNames() Gets the names of each of the key columns produced for a single run.
java.lang.Object[]	getKeyTypes() Gets the data types of each of the key columns produced for a single run.
double	getMeasure(java.lang.String additionalMeasureName) Returns the value of the named measure
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
boolean	getPredTargetColumn()
java.lang.String	getRawResultOutput() Gets the raw output from the classifier
java.lang.Object[]	getResult(Instances train, Instances test) Gets the results for the supplied train and test datasets.
java.lang.String[]	getResultNames() Gets the names of each of the result columns produced for a single run.
java.lang.Object[]	getResultTypes() Gets the data types of each of the result columns produced for a single run.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	globalInfo() Returns a string describing this split evaluator
java.util.Enumeration	listOptions() Returns an enumeration describing the available options..
void	setAdditionalMeasures(java.lang.String[] additionalMeasures) Set a list of method names for additional measures to look for in Classifiers.
void	setAttributeID(int v) Set the index of Attibute Identifying the instances
void	setClassForIRStatistics(int v) Set the value of ClassForIRStatistics.
void	setClassifier(Classifier newClassifier) Sets the classifier.
void	setClassifierName(java.lang.String newClassifierName) Set the Classifier to use, given it's class name.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setPredTargetColumn(boolean v) Set the flag for prediction and target output.
java.lang.String	toString() Returns a text description of the split evaluator.

Methods inherited from class java.lang.Object

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

Constructor Detail

ClassifierSplitEvaluator

public ClassifierSplitEvaluator()

No args constructor.

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this split evaluator

Returns:

a description of the split evaluator suitable for displaying in the explorer/experimenter gui

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options..

Specified by:

listOptions in interface OptionHandler

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 <class name>
  The full class name of the classifier.
  eg: weka.classifiers.bayes.NaiveBayes
 

 -C <index>
  The index of the class for which IR statistics
  are to be output. (default 1)
 

 -I <index>
  The index of an attribute to output in the
  results. This attribute should identify an
  instance in order to know which instances are
  in the test set of a cross validation. if 0
  no output (default 0).
 

 -P
  Add target and prediction columns to the result
  for each fold.
 

 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
 

All options after -- will be passed to the classifier.

Specified by:

setOptions in interface OptionHandler

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

Returns:

an array of strings suitable for passing to setOptions

setAdditionalMeasures

public void setAdditionalMeasures(java.lang.String[] additionalMeasures)

Set a list of method names for additional measures to look for in Classifiers. This could contain many measures (of which only a subset may be produceable by the current Classifier) if an experiment is the type that iterates over a set of properties.

Specified by:

setAdditionalMeasures in interface SplitEvaluator

Parameters:

additionalMeasures - a list of method names

enumerateMeasures

public java.util.Enumeration enumerateMeasures()

Returns an enumeration of any additional measure names that might be in the classifier

Specified by:

enumerateMeasures in interface AdditionalMeasureProducer

Returns:

an enumeration of the measure names

getMeasure

public double getMeasure(java.lang.String additionalMeasureName)

Returns the value of the named measure

Specified by:

getMeasure in interface AdditionalMeasureProducer

Parameters:

additionalMeasureName - the name of the measure to query for its value

Returns:

the value of the named measure

Throws:

java.lang.IllegalArgumentException - if the named measure is not supported

getKeyTypes

public java.lang.Object[] getKeyTypes()

Gets the data types of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.

Specified by:

getKeyTypes in interface SplitEvaluator

Returns:

an array containing objects of the type of each key column. The objects should be Strings, or Doubles.

getKeyNames

public java.lang.String[] getKeyNames()

Gets the names of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.

Specified by:

getKeyNames in interface SplitEvaluator

Returns:

an array containing the name of each key column

getKey

public java.lang.Object[] getKey()

Gets the key describing the current SplitEvaluator. For example This may contain the name of the classifier used for classifier predictive evaluation. The number of key fields must be constant for a given SplitEvaluator.

Specified by:

getKey in interface SplitEvaluator

Returns:

an array of objects containing the key.

getResultTypes

public java.lang.Object[] getResultTypes()

Gets the data types of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.

Specified by:

getResultTypes in interface SplitEvaluator

Returns:

an array containing objects of the type of each result column. The objects should be Strings, or Doubles.

getResultNames

public java.lang.String[] getResultNames()

Gets the names of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.

Specified by:

getResultNames in interface SplitEvaluator

Returns:

an array containing the name of each result column

getResult

public java.lang.Object[] getResult(Instances train,
                                    Instances test)
                             throws java.lang.Exception

Gets the results for the supplied train and test datasets. Now performs a deep copy of the classifier before it is built and evaluated (just in case the classifier is not initialized properly in buildClassifier()).

Specified by:

getResult in interface SplitEvaluator

Parameters:

train - the training Instances.

test - the testing Instances.

Returns:

the results stored in an array. The objects stored in the array may be Strings, Doubles, or null (for the missing value).

Throws:

java.lang.Exception - if a problem occurs while getting the results

classifierTipText

public java.lang.String classifierTipText()

Returns the tip text for this property

Returns:

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

getClassifier

public Classifier getClassifier()

Get the value of Classifier.

Returns:

Value of Classifier.

setClassifier

public void setClassifier(Classifier newClassifier)

Sets the classifier.

Parameters:

newClassifier - the new classifier to use.

getClassForIRStatistics

public int getClassForIRStatistics()

Get the value of ClassForIRStatistics.

Returns:

Value of ClassForIRStatistics.

setClassForIRStatistics

public void setClassForIRStatistics(int v)

Set the value of ClassForIRStatistics.

Parameters:

v - Value to assign to ClassForIRStatistics.

getAttributeID

public int getAttributeID()

Get the index of Attibute Identifying the instances

Returns:

index of outputed Attribute.

setAttributeID

public void setAttributeID(int v)

Set the index of Attibute Identifying the instances

Parameters:

v - index the attribute to output

getPredTargetColumn

public boolean getPredTargetColumn()

Returns:

true if the prediction and target columns must be outputed.

setPredTargetColumn

public void setPredTargetColumn(boolean v)

Set the flag for prediction and target output.

Parameters:

v - true if the 2 columns have to be outputed. false otherwise.

setClassifierName

public void setClassifierName(java.lang.String newClassifierName)
                       throws java.lang.Exception

Set the Classifier to use, given it's class name. A new classifier will be instantiated.

Parameters:

newClassifierName - the Classifier class name.

Throws:

java.lang.Exception - if the class name is invalid.

getRawResultOutput

public java.lang.String getRawResultOutput()

Gets the raw output from the classifier

Specified by:

getRawResultOutput in interface SplitEvaluator

Returns:

the raw output from th,0e classifier

toString

public java.lang.String toString()

Returns a text description of the split evaluator.

Overrides:

toString in class java.lang.Object

Returns:

a text description of the split evaluator.

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Returns:

the revision