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## weka.attributeSelection
Class ClassifierAttributeEval

    java.lang.Object
      weka.attributeSelection.ASEvaluation
          weka.attributeSelection.ClassifierAttributeEval

All Implemented Interfaces:
  java.io.Serializable, AttributeEvaluator, CapabilitiesHandler, OptionHandler, RevisionHandler

    public class ClassifierAttributeEval

extends ASEvaluation
implements AttributeEvaluator, OptionHandler

ClassifierAttributeEval :
Evaluates the worth of an attribute by using a user-specified classifier.

Valid options are:

     -S <seed>
      Random number seed for cross validation.
      (default = 1)

     -F <folds>
      Number of folds for cross validation.
      (default = 10)

     -D
      Use training data for evaluation rather than cross validaton.

     -B <classname + options>
      Classifier to use.
      (default = OneR)

Version:
  $Revision: 5928 $
Author:
  Mark Hall (mhall@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
See Also:
  Serialized Form

Constructor Summary
`ClassifierAttributeEval()` Constructor.

Method Summary
`void` | `buildEvaluator(Instances data)` Initializes a ClassifierAttribute attribute evaluator.
`java.lang.String` | `classifierTipText()` Returns a string for this option suitable for display in the gui as a tip text.
`double` | `evaluateAttribute(int attribute)` Evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
`java.lang.String` | `evalUsingTrainingDataTipText()` Returns a string for this option suitable for display in the gui as a tip text.
`java.lang.String` | `foldsTipText()` Returns a string for this option suitable for display in the gui as a tip text.
`Capabilities` | `getCapabilities()` Returns the capabilities of this evaluator.
`Classifier` | `getClassifier()` Returns the classifier to use for evaluating the attribute.
`boolean` | `getEvalUsingTrainingData()` Returns true if the training data is to be used for evaluation.
`int` | `getFolds()` Get the number of folds used for cross validation.
`java.lang.String[]` | `getOptions()` returns the current setup.
`java.lang.String` | `getRevision()` Returns the revision string.
`int` | `getSeed()` Get the random number seed.
`java.lang.String` | `globalInfo()` Returns a string describing this attribute evaluator.
`java.util.Enumeration` | `listOptions()` Returns an enumeration describing the available options.
`static void` | `main(java.lang.String[] args)` Main method for executing this class.
`java.lang.String` | `seedTipText()` Returns a string for this option suitable for display in the gui as a tip text.
`void` | `setClassifier(Classifier value)` Set the classifier to use for evaluating the attribute.
`void` | `setEvalUsingTrainingData(boolean value)` Use the training data to evaluate attributes rather than cross validation.
`void` | `setFolds(int value)` Set the number of folds to use for cross validation.
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`void` | `setSeed(int value)` Set the random number seed for cross validation.
`java.lang.String` | `toString()` Return a description of the evaluator.

Methods inherited from class weka.attributeSelection.ASEvaluation
`forName, makeCopies, postProcess`

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

Constructor Detail

### ClassifierAttributeEval

    public ClassifierAttributeEval()

  Constructor.

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this attribute evaluator.

  Returns:
    a description of the 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:

       -S <seed>
        Random number seed for cross validation.
        (default = 1)

       -F <folds>
        Number of folds for cross validation.
        (default = 10)

       -D
        Use training data for evaluation rather than cross validaton.

       -B <classname + options>
        Classifier to use.
        (default = OneR)

  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()

  returns the current setup.

  Specified by:
    `getOptions` in interface `OptionHandler`
  Returns:
    the options of the current setup

### setSeed

    public void setSeed(int value)

  Set the random number seed for cross validation.

  Parameters:
    `value` - the seed to use

### getSeed

    public int getSeed()

  Get the random number seed.

  Returns:
    an `int` value

### seedTipText

    public java.lang.String seedTipText()

  Returns a string for this option suitable for display in the gui as a tip text.

  Returns:
    a string describing this option

### setFolds

    public void setFolds(int value)

  Set the number of folds to use for cross validation.

  Parameters:
    `value` - the number of folds

### getFolds

    public int getFolds()

  Get the number of folds used for cross validation.

  Returns:
    the number of folds

### foldsTipText

    public java.lang.String foldsTipText()

  Returns a string for this option suitable for display in the gui as a tip text.

  Returns:
    a string describing this option

### setEvalUsingTrainingData

    public void setEvalUsingTrainingData(boolean value)

  Use the training data to evaluate attributes rather than cross validation.

  Parameters:
    `value` - true if training data is to be used for evaluation

### getEvalUsingTrainingData

    public boolean getEvalUsingTrainingData()

  Returns true if the training data is to be used for evaluation.

  Returns:
    true if training data is to be used for evaluation

### evalUsingTrainingDataTipText

    public java.lang.String evalUsingTrainingDataTipText()

  Returns a string for this option suitable for display in the gui as a tip text.

  Returns:
    a string describing this option

### setClassifier

    public void setClassifier(Classifier value)

  Set the classifier to use for evaluating the attribute.

  Parameters:
    `value` - the classifier to use

### getClassifier

    public Classifier getClassifier()

  Returns the classifier to use for evaluating the attribute.

  Returns:
    the classifier in use

### classifierTipText

    public java.lang.String classifierTipText()

  Returns a string for this option suitable for display in the gui as a tip text.

  Returns:
    a string describing this option

### getCapabilities

    public Capabilities getCapabilities()

  Returns the capabilities of this evaluator.

  Specified by:
    `getCapabilities` in interface `CapabilitiesHandler`
  Overrides:
    `getCapabilities` in class `ASEvaluation`
  Returns:
    the capabilities of this evaluator
  See Also:
    `Capabilities`

### buildEvaluator

    public void buildEvaluator(Instances data)
                        throws java.lang.Exception

  Initializes a ClassifierAttribute attribute evaluator.

  Specified by:
    `buildEvaluator` in class `ASEvaluation`
  Parameters:
    `data` - set of instances serving as training data
  Throws:
    `java.lang.Exception` - if the evaluator has not been generated successfully

### evaluateAttribute

    public double evaluateAttribute(int attribute)
                             throws java.lang.Exception

  Evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.

  Specified by:
    `evaluateAttribute` in interface `AttributeEvaluator`
  Parameters:
    `attribute` - the index of the attribute to be evaluated
  Returns:
    the evaluation
  Throws:
    `java.lang.Exception` - if the attribute could not be evaluated

### toString

    public java.lang.String toString()

  Return a description of the evaluator.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    description as a string

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Overrides:
    `getRevision` in class `ASEvaluation`
  Returns:
    the revision

### main

    public static void main(java.lang.String[] args)

  Main method for executing this class.

  Parameters:
    `args` - the options

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