Package weka.experiment

Class ClassifierSplitEvaluator

java.lang.Object
weka.experiment.ClassifierSplitEvaluator
All Implemented Interfaces:
Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, SplitEvaluator
Direct Known Subclasses:
CostSensitiveClassifierSplitEvaluator
public class ClassifierSplitEvaluator extends 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:

  • Constructor Details

    • ClassifierSplitEvaluator

      public ClassifierSplitEvaluator()
      No args constructor.

  • Method Details

    • globalInfo

      public 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 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(String[] options) throws 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:
      Exception - if an option is not supported

    • getOptions

      public 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(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 Enumeration<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(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:
      IllegalArgumentException - if the named measure is not supported

    • getKeyTypes

      public 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 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 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 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 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 Object[] getResult(Instances train, Instances test) throws 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:
      Exception - if a problem occurs while getting the results

    • classifierTipText

      public 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 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(String newClassifierName) throws Exception
      Set the Classifier to use, given it's class name. A new classifier will be instantiated.
      Parameters:
      newClassifierName - the Classifier class name.
      Throws:
      Exception - if the class name is invalid.

    • getRawResultOutput

      public 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 String toString()
      Returns a text description of the split evaluator.
      Overrides:
      toString in class Object
      Returns:
      a text description of the split evaluator.

    • getRevision

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