VFI

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.misc.VFI

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler, weka.core.WeightedInstancesHandler

public class VFI
extends weka.classifiers.AbstractClassifier
implements weka.core.OptionHandler, weka.core.WeightedInstancesHandler, weka.core.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: 10390 $
Author:: Mark Hall (mhall@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary
- Fields inherited from class weka.classifiers.AbstractClassifier
  BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors
Constructor and Description

VFI()

Constructors
Constructor and Description
`VFI()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`biasTipText()` Returns the tip text for this property
`void`	`buildClassifier(weka.core.Instances instances)` Generates the classifier.
`double[]`	`distributionForInstance(weka.core.Instance instance)` Classifies the given test instance.
`double`	`getBias()` Get the value of the bias parameter
`weka.core.Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`java.lang.String[]`	`getOptions()` Gets the current settings of VFI
`java.lang.String`	`getRevision()` Returns the revision string.
`weka.core.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.
`boolean`	`getWeightByConfidence()` Get whether feature intervals are being weighted by confidence
`java.lang.String`	`globalInfo()` Returns a string describing this search method
`java.util.Enumeration<weka.core.Option>`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] args)` Main method for testing this class.
`void`	`setBias(double b)` Set the value of the exponential bias towards more confident intervals
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setWeightByConfidence(boolean c)` Set weighting by confidence
`java.lang.String`	`toString()` Returns a description of this classifier.
`java.lang.String`	`weightByConfidenceTipText()` Returns the tip text for this property

Methods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

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

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - VFI
```
public VFI()
```
- 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
  - getTechnicalInformation
```
public weka.core.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 weka.core.TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - listOptions
```
public java.util.Enumeration<weka.core.Option> listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    listOptions in class weka.classifiers.AbstractClassifier
    
    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:
```
 -C
  Don't weight voting intervals by confidence
 
```
```
 -B <bias>
  Set exponential bias towards confident intervals
  (default = 0.6)
 
```
    Specified by:
    
    setOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    setOptions in class weka.classifiers.AbstractClassifier
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - weightByConfidenceTipText
```
public java.lang.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 java.lang.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 java.lang.String[] getOptions()
```
    Gets the current settings of VFI
    
    Specified by:
    
    getOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    getOptions in class weka.classifiers.AbstractClassifier
    
    Returns:
    
    an array of strings suitable for passing to setOptions()
  - getCapabilities
```
public weka.core.Capabilities getCapabilities()
```
    Returns default capabilities of the classifier.
    
    Specified by:
    
    getCapabilities in interface weka.classifiers.Classifier
    
    Specified by:
    
    getCapabilities in interface weka.core.CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class weka.classifiers.AbstractClassifier
    
    Returns:
    
    the capabilities of this classifier
  - buildClassifier
```
public void buildClassifier(weka.core.Instances instances)
                     throws java.lang.Exception
```
    Generates the classifier.
    
    Specified by:
    
    buildClassifier in interface weka.classifiers.Classifier
    
    Parameters:
    
    instances - set of instances serving as training data
    
    Throws:
    
    java.lang.Exception - if the classifier has not been generated successfully
  - toString
```
public java.lang.String toString()
```
    Returns a description of this classifier.
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a description of this classifier as a string.
  - distributionForInstance
```
public double[] distributionForInstance(weka.core.Instance instance)
                                 throws java.lang.Exception
```
    Classifies the given test instance.
    
    Specified by:
    
    distributionForInstance in interface weka.classifiers.Classifier
    
    Overrides:
    
    distributionForInstance in class weka.classifiers.AbstractClassifier
    
    Parameters:
    
    instance - the instance to be classified
    
    Returns:
    
    the predicted class for the instance
    
    Throws:
    
    java.lang.Exception - if the instance can't be classified
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface weka.core.RevisionHandler
    
    Overrides:
    
    getRevision in class weka.classifiers.AbstractClassifier
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] args)
```
    Main method for testing this class.
    
    Parameters:
    
    args - should contain command line arguments for evaluation (see Evaluation).

Class VFI

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

VFI

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

weightByConfidenceTipText

setWeightByConfidence

getWeightByConfidence

biasTipText

setBias

getBias

getOptions

getCapabilities

buildClassifier

toString

distributionForInstance

getRevision

main