weka.attributeSelection
Class ConsistencySubsetEval

java.lang.Object
  weka.attributeSelection.ASEvaluation
      weka.attributeSelection.SubsetEvaluator
          weka.attributeSelection.ConsistencySubsetEval

All Implemented Interfaces:

java.io.Serializable

public class ConsistencySubsetEval

extends SubsetEvaluator

Consistency attribute subset evaluator.

For more information see:
Liu, H., and Setiono, R., (1996). A probabilistic approach to feature selection - A filter solution. In 13th International Conference on Machine Learning (ICML'96), July 1996, pp. 319-327. Bari, Italy.

Version:

$Revision: 1.10 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz)

See Also:

Serialized Form

Nested Class Summary

class

ConsistencySubsetEval.hashKey Class providing keys to the hash table.

Field Summary

private int	m_classIndex class index
private Discretize	m_disTransform Discretise numeric attributes
private int	m_numAttribs number of attributes in the training data
private int	m_numInstances number of instances in the training data
private java.util.Hashtable	m_table Hash table for evaluating feature subsets
private Instances	m_trainInstances training instances

Constructor Summary

ConsistencySubsetEval()
Constructor.

Method Summary

void	buildEvaluator(Instances data) Generates a attribute evaluator.
private double	consistencyCount() calculates the level of consistency in a dataset using a subset of features.
double	evaluateSubset(java.util.BitSet subset) Evaluates a subset of attributes
java.lang.String	globalInfo() Returns a string describing this search method
private void	insertIntoTable(Instance inst, double[] instA) Inserts an instance into the hash table
static void	main(java.lang.String[] args) Main method for testing this class.
private void	resetOptions() reset to defaults
java.lang.String	toString() returns a description of the evaluator

Methods inherited from class weka.attributeSelection.ASEvaluation

forName, makeCopies, postProcess

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_trainInstances

private Instances m_trainInstances

training instances

m_classIndex

private int m_classIndex

class index

m_numAttribs

private int m_numAttribs

number of attributes in the training data

m_numInstances

private int m_numInstances

number of instances in the training data

m_disTransform

private Discretize m_disTransform

Discretise numeric attributes

m_table

private java.util.Hashtable m_table

Hash table for evaluating feature subsets

Constructor Detail

ConsistencySubsetEval

public ConsistencySubsetEval()

Constructor. Calls restOptions to set default options

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this search method

Returns:

a description of the search suitable for displaying in the explorer/experimenter gui

resetOptions

private void resetOptions()

reset to defaults

buildEvaluator

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

Generates a attribute evaluator. Has to initialize all fields of the evaluator that are not being set via options.

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

evaluateSubset

public double evaluateSubset(java.util.BitSet subset)
                      throws java.lang.Exception

Evaluates a subset of attributes

Specified by:

evaluateSubset in class SubsetEvaluator

Parameters:

subset - a bitset representing the attribute subset to be evaluated

Returns:

the "merit" of the subset

Throws:

java.lang.Exception - if the subset could not be evaluated

consistencyCount

private double consistencyCount()

calculates the level of consistency in a dataset using a subset of features. The consistency of a hash table entry is the total number of instances hashed to that location minus the number of instances in the largest class hashed to that location. The total consistency is 1.0 minus the sum of the individual consistencies divided by the total number of instances.

Returns:

the consistency of the hash table as a value between 0 and 1.

insertIntoTable

private void insertIntoTable(Instance inst,
                             double[] instA)
                      throws java.lang.Exception

Inserts an instance into the hash table

Parameters:

inst - instance to be inserted

instA - the instance to be inserted as an array of attribute values.

Throws:

java.lang.Exception - if the instance can't be inserted

toString

public java.lang.String toString()

returns a description of the evaluator

Returns:

a description of the evaluator as a String.

main

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

Main method for testing this class.

Parameters:

args - the options