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.

 -no-size
  Skips the determination of sizes (train/test/classifier)
  (default: sizes are determined)

 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: 11323 $
Author:: Len Trigg (trigg@cs.waikato.ac.nz)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

ClassifierSplitEvaluator()
No args constructor.

Constructors
Constructor and Description
`ClassifierSplitEvaluator()` No args constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`classifierTipText()` Returns the tip text for this property
`java.util.Enumeration<java.lang.String>`	`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
`boolean`	`getNoSizeDetermination()` Returns whether the size determination (train/test/classifer) is skipped.
`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<Option>`	`listOptions()` Returns an enumeration describing the available options..
`java.lang.String`	`noSizeDeterminationTipText()` Returns the tip text for this property
`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`	`setNoSizeDetermination(boolean value)` Sets whether the size determination (train/test/classifer) is skipped.
`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

Methods inherited from interface weka.core.OptionHandler
makeCopy

- 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<Option> 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.
 
```
```
 -no-size
  Skips the determination of sizes (train/test/classifier)
  (default: sizes are determined)
 
```
```
 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<java.lang.String> 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.
  - getNoSizeDetermination
```
public boolean getNoSizeDetermination()
```
    Returns whether the size determination (train/test/classifer) is skipped.
    
    Returns:
    
    true if size determination skipped
  - setNoSizeDetermination
```
public void setNoSizeDetermination(boolean value)
```
    Sets whether the size determination (train/test/classifer) is skipped.
    
    Parameters:
    
    value - true if to determine sizes
  - noSizeDeterminationTipText
```
public java.lang.String noSizeDeterminationTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - 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

Class ClassifierSplitEvaluator

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

ClassifierSplitEvaluator

Method Detail

globalInfo

listOptions

setOptions

getOptions

setAdditionalMeasures

enumerateMeasures

getMeasure

getKeyTypes

getKeyNames

getKey

getResultTypes

getResultNames

getResult

classifierTipText

getClassifier

setClassifier

getClassForIRStatistics

setClassForIRStatistics

getAttributeID

setAttributeID

getPredTargetColumn

setPredTargetColumn

getNoSizeDetermination

setNoSizeDetermination

noSizeDeterminationTipText

setClassifierName

getRawResultOutput

toString

getRevision