weka.experiment

## Class CostSensitiveClassifierSplitEvaluator

- java.lang.Object
- - weka.experiment.ClassifierSplitEvaluator
  - - weka.experiment.CostSensitiveClassifierSplitEvaluator

- All Implemented Interfaces:
    java.io.Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, SplitEvaluator

      public class CostSensitiveClassifierSplitEvaluator
      extends ClassifierSplitEvaluator

  SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.

  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

       -D <directory>
        Name of a directory to search for cost files when loading
        costs on demand (default current directory).

  All options after -- will be passed to the classifier.
  Version:
    $Revision: 11323 $
  Author:
    Len Trigg (len@reeltwo.com)
  See Also:
    Serialized Form

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `CostSensitiveClassifierSplitEvaluator()`

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `java.io.File` | `getOnDemandDirectory()` Returns the directory that will be searched for cost files when loading on demand.
    `java.lang.String[]` | `getOptions()` Gets the current settings of 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` | `onDemandDirectoryTipText()` Returns the tip text for this property
    `void` | `setOnDemandDirectory(java.io.File newDir)` Sets the directory that will be searched for cost files when loading on demand.
    `void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
    `java.lang.String` | `toString()` Returns a text description of the split evaluator.

    - ### Methods inherited from class weka.experiment.ClassifierSplitEvaluator

      `classifierTipText, enumerateMeasures, getAttributeID, getClassForIRStatistics, getClassifier, getKey, getKeyNames, getKeyTypes, getMeasure, getNoSizeDetermination, getPredTargetColumn, getRawResultOutput, noSizeDeterminationTipText, setAdditionalMeasures, setAttributeID, setClassForIRStatistics, setClassifier, setClassifierName, setNoSizeDetermination, setPredTargetColumn`

    - ### Methods inherited from class java.lang.Object

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

- - ### Constructor Detail

    - #### CostSensitiveClassifierSplitEvaluator

          public CostSensitiveClassifierSplitEvaluator()

  - ### Method Detail

    - #### globalInfo

          public java.lang.String globalInfo()

      Returns a string describing this split evaluator
      Overrides:
        `globalInfo` in class `ClassifierSplitEvaluator`
      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`
      Overrides:
        `listOptions` in class `ClassifierSplitEvaluator`
      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

           -D <directory>
            Name of a directory to search for cost files when loading
            costs on demand (default current directory).

      All options after -- will be passed to the classifier.
      Specified by:
        `setOptions` in interface `OptionHandler`
      Overrides:
        `setOptions` in class `ClassifierSplitEvaluator`
      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 `ClassifierSplitEvaluator`
      Returns:
        an array of strings suitable for passing to setOptions

    - #### onDemandDirectoryTipText

          public java.lang.String onDemandDirectoryTipText()

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

    - #### getOnDemandDirectory

          public java.io.File getOnDemandDirectory()

      Returns the directory that will be searched for cost files when loading on demand.
      Returns:
        The cost file search directory.

    - #### setOnDemandDirectory

          public void setOnDemandDirectory(java.io.File newDir)

      Sets the directory that will be searched for cost files when loading on demand.
      Parameters:
        `newDir` - The cost file search directory.

    - #### 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`
      Overrides:
        `getResultTypes` in class `ClassifierSplitEvaluator`
      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`
      Overrides:
        `getResultNames` in class `ClassifierSplitEvaluator`
      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`
      Overrides:
        `getResult` in class `ClassifierSplitEvaluator`
      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

    - #### toString

          public java.lang.String toString()

      Returns a text description of the split evaluator.
      Overrides:
        `toString` in class `ClassifierSplitEvaluator`
      Returns:
        a text description of the split evaluator.

    - #### getRevision

          public java.lang.String getRevision()

      Returns the revision string.
      Specified by:
        `getRevision` in interface `RevisionHandler`
      Overrides:
        `getRevision` in class `ClassifierSplitEvaluator`
      Returns:
        the revision