Constructor Detail

• AttributeSelectedClassifier

  public AttributeSelectedClassifier()

  Default constructor.

Method Detail

• globalInfo

  public java.lang.String globalInfo()

  Returns a string describing this search method

  Returns:

  a description of the search method 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

  Overrides:

  listOptions in class SingleClassifierEnhancer

  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:

   -E <attribute evaluator specification>
    Full class name of attribute evaluator, followed
    by its options.
    eg: "weka.attributeSelection.CfsSubsetEval -L"
    (default weka.attributeSelection.CfsSubsetEval)

   -S <search method specification>
    Full class name of search method, followed
    by its options.
    eg: "weka.attributeSelection.BestFirst -D 1"
    (default weka.attributeSelection.BestFirst)

   -D
    If set, classifier is run in debug mode and
    may output additional info to the console

   -W
    Full name of base classifier.
    (default: weka.classifiers.trees.J48)

   
   Options specific to classifier weka.classifiers.trees.J48:
   

   -U
    Use unpruned tree.

   -C <pruning confidence>
    Set confidence threshold for pruning.
    (default 0.25)

   -M <minimum number of instances>
    Set minimum number of instances per leaf.
    (default 2)

   -R
    Use reduced error pruning.

   -N <number of folds>
    Set number of folds for reduced error
    pruning. One fold is used as pruning set.
    (default 3)

   -B
    Use binary splits only.

   -S
    Don't perform subtree raising.

   -L
    Do not clean up after the tree has been built.

   -A
    Laplace smoothing for predicted probabilities.

   -Q <seed>
    Seed for random data shuffling (default 1).

  Specified by:

  setOptions in interface OptionHandler

  Overrides:

  setOptions in class SingleClassifierEnhancer

  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 SingleClassifierEnhancer

  Returns:

  an array of strings suitable for passing to setOptions

• evaluatorTipText

  public java.lang.String evaluatorTipText()

  Returns the tip text for this property

  Returns:

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

• setEvaluator

  public void setEvaluator​(ASEvaluation evaluator)

  Sets the attribute evaluator

  Parameters:

  evaluator - the evaluator with all options set.

• getEvaluator

  public ASEvaluation getEvaluator()

  Gets the attribute evaluator used

  Returns:

  the attribute evaluator

• searchTipText

  public java.lang.String searchTipText()

  Returns the tip text for this property

  Returns:

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

• setSearch

  public void setSearch​(ASSearch search)

  Sets the search method

  Parameters:

  search - the search method with all options set.

• getSearch

  public ASSearch getSearch()

  Gets the search method used

  Returns:

  the search method

• getCapabilities

  public Capabilities getCapabilities()

  Returns default capabilities of the classifier.

  Specified by:

  getCapabilities in interface CapabilitiesHandler

  Overrides:

  getCapabilities in class SingleClassifierEnhancer

  Returns:

  the capabilities of this classifier

  See Also:

  Capabilities

• buildClassifier

  public void buildClassifier​(Instances data)
                       throws java.lang.Exception

  Build the classifier on the dimensionally reduced data.

  Specified by:

  buildClassifier in class Classifier

  Parameters:

  data - the training data

  Throws:

  java.lang.Exception - if the classifier could not be built successfully

• distributionForInstance

  public double[] distributionForInstance​(Instance instance)
                                   throws java.lang.Exception

  Classifies a given instance after attribute selection

  Overrides:

  distributionForInstance in class Classifier

  Parameters:

  instance - the instance to be classified

  Returns:

  the class distribution

  Throws:

  java.lang.Exception - if instance could not be classified successfully

• graphType

  public int graphType()

  Returns the type of graph this classifier represents.

  Specified by:

  graphType in interface Drawable

  Returns:

  the type of graph

• graph

  public java.lang.String graph()
                         throws java.lang.Exception

  Returns graph describing the classifier (if possible).

  Specified by:

  graph in interface Drawable

  Returns:

  the graph of the classifier in dotty format

  Throws:

  java.lang.Exception - if the classifier cannot be graphed

• toString

  public java.lang.String toString()

  Output a representation of this classifier

  Overrides:

  toString in class java.lang.Object

  Returns:

  a representation of this classifier

• measureNumAttributesSelected

  public double measureNumAttributesSelected()

  Additional measure --- number of attributes selected

  Returns:

  the number of attributes selected

• measureSelectionTime

  public double measureSelectionTime()

  Additional measure --- time taken (milliseconds) to select the attributes

  Returns:

  the time taken to select attributes

• measureTime

  public double measureTime()

  Additional measure --- time taken (milliseconds) to select attributes and build the classifier

  Returns:

  the total time (select attributes + build classifier)

• enumerateMeasures

  public java.util.Enumeration enumerateMeasures()

  Returns an enumeration of the additional measure names

  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

• getRevision

  public java.lang.String getRevision()

  Returns the revision string.

  Specified by:

  getRevision in interface RevisionHandler

  Overrides:

  getRevision in class Classifier

  Returns:

  the revision

• main

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

  Main method for testing this class.

  Parameters:

  argv - should contain the following arguments: -t training file [-T test file] [-c class index]