Package weka.classifiers.misc

Class VFI

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.misc.VFI
All Implemented Interfaces:
Serializable, Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler
public class VFI extends Classifier implements OptionHandler, WeightedInstancesHandler, TechnicalInformationHandler
Classification by voting feature intervals. Intervals are constucted around each class for each attribute (basically discretization). Class counts are recorded for each interval on each attribute. Classification is by voting. For more info see:

G. Demiroz, A. Guvenir: Classification by voting feature intervals. In: 9th European Conference on Machine Learning, 85-92, 1997.

Have added a simple attribute weighting scheme. Higher weight is assigned to more confident intervals, where confidence is a function of entropy:
weight (att_i) = (entropy of class distrib att_i / max uncertainty)^-bias

BibTeX: 

 @inproceedings{Demiroz1997,
    author = {G. Demiroz and A. Guvenir},
    booktitle = {9th European Conference on Machine Learning},
    pages = {85-92},
    publisher = {Springer},
    title = {Classification by voting feature intervals},
    year = {1997}
 }

Faster than NaiveBayes but slower than HyperPipes. 

  Confidence: 0.01 (two tailed)

 Dataset                   (1) VFI '-B  | (2) Hyper (3) Naive
                         ------------------------------------
 anneal.ORIG               (10)   74.56 |   97.88 v   74.77
 anneal                    (10)   71.83 |   97.88 v   86.51 v
 audiology                 (10)   51.69 |   66.26 v   72.25 v
 autos                     (10)   57.63 |   62.79 v   57.76
 balance-scale             (10)   68.72 |   46.08 *   90.5  v
 breast-cancer             (10)   67.25 |   69.84 v   73.12 v
 wisconsin-breast-cancer   (10)   95.72 |   88.31 *   96.05 v
 horse-colic.ORIG          (10)   66.13 |   70.41 v   66.12
 horse-colic               (10)   78.36 |   62.07 *   78.28
 credit-rating             (10)   85.17 |   44.58 *   77.84 *
 german_credit             (10)   70.81 |   69.89 *   74.98 v
 pima_diabetes             (10)   62.13 |   65.47 v   75.73 v
 Glass                     (10)   56.82 |   50.19 *   47.43 *
 cleveland-14-heart-diseas (10)   80.01 |   55.18 *   83.83 v
 hungarian-14-heart-diseas (10)   82.8  |   65.55 *   84.37 v
 heart-statlog             (10)   79.37 |   55.56 *   84.37 v
 hepatitis                 (10)   83.78 |   63.73 *   83.87
 hypothyroid               (10)   92.64 |   93.33 v   95.29 v
 ionosphere                (10)   94.16 |   35.9  *   82.6  *
 iris                      (10)   96.2  |   91.47 *   95.27 *
 kr-vs-kp                  (10)   88.22 |   54.1  *   87.84 *
 labor                     (10)   86.73 |   87.67     93.93 v
 lymphography              (10)   78.48 |   58.18 *   83.24 v
 mushroom                  (10)   99.85 |   99.77 *   95.77 *
 primary-tumor             (10)   29    |   24.78 *   49.35 v
 segment                   (10)   77.42 |   75.15 *   80.1  v
 sick                      (10)   65.92 |   93.85 v   92.71 v
 sonar                     (10)   58.02 |   57.17     67.97 v
 soybean                   (10)   86.81 |   86.12 *   92.9  v
 splice                    (10)   88.61 |   41.97 *   95.41 v
 vehicle                   (10)   52.94 |   32.77 *   44.8  *
 vote                      (10)   91.5  |   61.38 *   90.19 *
 vowel                     (10)   57.56 |   36.34 *   62.81 v
 waveform                  (10)   56.33 |   46.11 *   80.02 v
 zoo                       (10)   94.05 |   94.26     95.04 v
                          ------------------------------------
                                (v| |*) |  (9|3|23)  (22|5|8)

Valid options are: 

 -C
  Don't weight voting intervals by confidence
 -B <bias>
  Set exponential bias towards confident intervals
  (default = 0.6)
Version:
$Revision: 7180 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • VFI

      public VFI()

  • Method Details

    • globalInfo

      public String globalInfo()
      Returns a string describing this search method
      Returns:
      a description of the search method suitable for displaying in the explorer/experimenter gui

    • getTechnicalInformation

      public TechnicalInformation getTechnicalInformation()
      Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
      Specified by:
      getTechnicalInformation in interface TechnicalInformationHandler
      Returns:
      the technical information about this class

    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class Classifier
      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: 

       -C
  Don't weight voting intervals by confidence
       -B <bias>
  Set exponential bias towards confident intervals
  (default = 1.0)
      Specified by:
      setOptions in interface OptionHandler
      Overrides:
      setOptions in class Classifier
      Parameters:
      options - the list of options as an array of strings
      Throws:
      Exception - if an option is not supported

    • weightByConfidenceTipText

      public String weightByConfidenceTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • setWeightByConfidence

      public void setWeightByConfidence(boolean c)
      Set weighting by confidence
      Parameters:
      c - true if feature intervals are to be weighted by confidence

    • getWeightByConfidence

      public boolean getWeightByConfidence()
      Get whether feature intervals are being weighted by confidence
      Returns:
      true if weighting by confidence is selected

    • biasTipText

      public String biasTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • setBias

      public void setBias(double b)
      Set the value of the exponential bias towards more confident intervals
      Parameters:
      b - the value of the bias parameter

    • getBias

      public double getBias()
      Get the value of the bias parameter
      Returns:
      the bias parameter

    • getOptions

      public String[] getOptions()
      Gets the current settings of VFI
      Specified by:
      getOptions in interface OptionHandler
      Overrides:
      getOptions in class Classifier
      Returns:
      an array of strings suitable for passing to setOptions()

    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      Specified by:
      getCapabilities in interface CapabilitiesHandler
      Overrides:
      getCapabilities in class Classifier
      Returns:
      the capabilities of this classifier
      See Also:

    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Generates the classifier.
      Specified by:
      buildClassifier in class Classifier
      Parameters:
      instances - set of instances serving as training data
      Throws:
      Exception - if the classifier has not been generated successfully

    • toString

      public String toString()
      Returns a description of this classifier.
      Overrides:
      toString in class Object
      Returns:
      a description of this classifier as a string.

    • distributionForInstance

      public double[] distributionForInstance(Instance instance) throws Exception
      Classifies the given test instance.
      Overrides:
      distributionForInstance in class Classifier
      Parameters:
      instance - the instance to be classified
      Returns:
      the predicted class for the instance
      Throws:
      Exception - if the instance can't be classified

    • getRevision

      public 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(String[] args)
      Main method for testing this class.
      Parameters:
      args - should contain command line arguments for evaluation (see Evaluation).