weka.filters
Class DiscretizeFilter

java.lang.Object
  extended by weka.filters.Filter
      extended by weka.filters.DiscretizeFilter
All Implemented Interfaces:
java.io.Serializable, OptionHandler, WeightedInstancesHandler

public class DiscretizeFilter
extends Filter
implements OptionHandler, WeightedInstancesHandler

An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. Discretization can be either by simple binning, or by Fayyad & Irani's MDL method (the default).

Valid filter-specific options are:

-B num
Specifies the (maximum) number of bins to divide numeric attributes into. (default: class-based discretisation).

-F
Use equal-frequency instead of equal-width discretization if class-based discretisation is turned off.

-O
Optimize the number of bins using a leave-one-out estimate of the entropy (for equal-width binning).

-R col1,col2-col4,...
Specifies list of columns to Discretize. First and last are valid indexes. (default: none)

-V
Invert matching sense.

-D
Make binary nominal attributes.

-E
Use better encoding of split point for MDL.

-K
Use Kononeko's MDL criterion.

Version:
$Revision: 1.1 $
Author:
Len Trigg ([email protected]), Eibe Frank ([email protected])
See Also:
Serialized Form

Constructor Summary
DiscretizeFilter()
          Constructor - initialises the filter
 
Method Summary
 java.lang.String attributeIndicesTipText()
          Returns the tip text for this property
 boolean batchFinished()
          Signifies that this batch of input to the filter is finished.
 java.lang.String binsTipText()
          Returns the tip text for this property
 java.lang.String findNumBinsTipText()
          Returns the tip text for this property
 java.lang.String getAttributeIndices()
          Gets the current range selection
 int getBins()
          Gets the number of bins numeric attributes will be divided into
 double[] getCutPoints(int attributeIndex)
          Gets the cut points for an attribute
 boolean getFindNumBins()
          Get the value of FindNumBins.
 boolean getInvertSelection()
          Gets whether the supplied columns are to be removed or kept
 boolean getMakeBinary()
          Gets whether binary attributes should be made for discretized ones.
 java.lang.String[] getOptions()
          Gets the current settings of the filter.
 boolean getUseBetterEncoding()
          Gets whether better encoding is to be used for MDL.
 boolean getUseEqualFrequency()
          Get the value of UseEqualFrequency.
 boolean getUseKononenko()
          Gets whether Kononenko's MDL criterion is to be used.
 boolean getUseMDL()
          Gets whether MDL will be used as the discretisation method.
 java.lang.String globalInfo()
          Returns a string describing this filter
 boolean input(Instance instance)
          Input an instance for filtering.
 java.lang.String invertSelectionTipText()
          Returns the tip text for this property
 java.util.Enumeration listOptions()
          Gets an enumeration describing the available options
static void main(java.lang.String[] argv)
          Main method for testing this class.
 java.lang.String makeBinaryTipText()
          Returns the tip text for this property
 void setAttributeIndices(java.lang.String rangeList)
          Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
 void setAttributeIndicesArray(int[] attributes)
          Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
 void setBins(int numBins)
          Sets the number of bins to divide each selected numeric attribute into
 void setFindNumBins(boolean newFindNumBins)
          Set the value of FindNumBins.
 boolean setInputFormat(Instances instanceInfo)
          Sets the format of the input instances.
 void setInvertSelection(boolean invert)
          Sets whether selected columns should be removed or kept.
 void setMakeBinary(boolean makeBinary)
          Sets whether binary attributes should be made for discretized ones.
 void setOptions(java.lang.String[] options)
          Parses the options for this object.
 void setUseBetterEncoding(boolean useBetterEncoding)
          Sets whether better encoding is to be used for MDL.
 void setUseEqualFrequency(boolean newUseEqualFrequency)
          Set the value of UseEqualFrequency.
 void setUseKononenko(boolean useKon)
          Sets whether Kononenko's MDL criterion is to be used.
 void setUseMDL(boolean useMDL)
          Sets whether MDL will be used as the discretisation method.
 java.lang.String useBetterEncodingTipText()
          Returns the tip text for this property
 java.lang.String useKononenkoTipText()
          Returns the tip text for this property
 java.lang.String useMDLTipText()
          Returns the tip text for this property
 
Methods inherited from class weka.filters.Filter
batchFilterFile, filterFile, getOutputFormat, inputFormat, isOutputFormatDefined, numPendingOutput, output, outputFormat, outputPeek, useFilter
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

DiscretizeFilter

public DiscretizeFilter()
Constructor - initialises the filter

Method Detail

listOptions

public java.util.Enumeration listOptions()
Gets 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 the options for this object. Valid options are:

-B num
Specifies the (maximum) number of bins to divide numeric attributes into. (default class-based discretisation).

-F
Use equal-frequency instead of equal-width discretization if class-based discretisation is turned off.

-O
Optimize the number of bins using a leave-one-out estimate of the entropy (for equal-width binning).

-R col1,col2-col4,...
Specifies list of columns to Discretize. First and last are valid indexes. (default none)

-V
Invert matching sense.

-D
Make binary nominal attributes.

-E
Use better encoding of split point for MDL.

-K
Use Kononeko's MDL criterion.

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()
Gets the current settings of the filter.

Specified by:
getOptions in interface OptionHandler
Returns:
an array of strings suitable for passing to setOptions

setInputFormat

public boolean setInputFormat(Instances instanceInfo)
                       throws java.lang.Exception
Sets the format of the input instances.

Overrides:
setInputFormat in class Filter
Parameters:
instanceInfo - an Instances object containing the input instance structure (any instances contained in the object are ignored - only the structure is required).
Returns:
true if the outputFormat may be collected immediately
Throws:
java.lang.Exception - if the input format can't be set successfully

input

public boolean input(Instance instance)
Input an instance for filtering. Ordinarily the instance is processed and made available for output immediately. Some filters require all instances be read before producing output.

Overrides:
input in class Filter
Parameters:
instance - the input instance
Returns:
true if the filtered instance may now be collected with output().
Throws:
java.lang.IllegalStateException - if no input format has been defined.

batchFinished

public boolean batchFinished()
Signifies that this batch of input to the filter is finished. If the filter requires all instances prior to filtering, output() may now be called to retrieve the filtered instances.

Overrides:
batchFinished in class Filter
Returns:
true if there are instances pending output
Throws:
java.lang.IllegalStateException - if no input structure has been defined

globalInfo

public java.lang.String globalInfo()
Returns a string describing this filter

Returns:
a description of the filter suitable for displaying in the explorer/experimenter gui

findNumBinsTipText

public java.lang.String findNumBinsTipText()
Returns the tip text for this property

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

getFindNumBins

public boolean getFindNumBins()
Get the value of FindNumBins.

Returns:
Value of FindNumBins.

setFindNumBins

public void setFindNumBins(boolean newFindNumBins)
Set the value of FindNumBins.

Parameters:
newFindNumBins - Value to assign to FindNumBins.

makeBinaryTipText

public java.lang.String makeBinaryTipText()
Returns the tip text for this property

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

getMakeBinary

public boolean getMakeBinary()
Gets whether binary attributes should be made for discretized ones.

Returns:
true if attributes will be binarized

setMakeBinary

public void setMakeBinary(boolean makeBinary)
Sets whether binary attributes should be made for discretized ones.

Parameters:
makeBinary - if binary attributes are to be made

useMDLTipText

public java.lang.String useMDLTipText()
Returns the tip text for this property

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

getUseMDL

public boolean getUseMDL()
Gets whether MDL will be used as the discretisation method.

Returns:
true if so, false if fixed bins should be used.

setUseMDL

public void setUseMDL(boolean useMDL)
Sets whether MDL will be used as the discretisation method.

Parameters:
useMDL - true if MDL should be used, false if fixed bins should be used.

useKononenkoTipText

public java.lang.String useKononenkoTipText()
Returns the tip text for this property

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

getUseEqualFrequency

public boolean getUseEqualFrequency()
Get the value of UseEqualFrequency.

Returns:
Value of UseEqualFrequency.

setUseEqualFrequency

public void setUseEqualFrequency(boolean newUseEqualFrequency)
Set the value of UseEqualFrequency.

Parameters:
newUseEqualFrequency - Value to assign to UseEqualFrequency.

getUseKononenko

public boolean getUseKononenko()
Gets whether Kononenko's MDL criterion is to be used.

Returns:
true if Kononenko's criterion will be used.

setUseKononenko

public void setUseKononenko(boolean useKon)
Sets whether Kononenko's MDL criterion is to be used.

Parameters:
useKon - true if Kononenko's one is to be used

useBetterEncodingTipText

public java.lang.String useBetterEncodingTipText()
Returns the tip text for this property

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

getUseBetterEncoding

public boolean getUseBetterEncoding()
Gets whether better encoding is to be used for MDL.

Returns:
true if the better MDL encoding will be used

setUseBetterEncoding

public void setUseBetterEncoding(boolean useBetterEncoding)
Sets whether better encoding is to be used for MDL.

Parameters:
useBetterEncoding - true if better encoding to be used.

binsTipText

public java.lang.String binsTipText()
Returns the tip text for this property

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

getBins

public int getBins()
Gets the number of bins numeric attributes will be divided into

Returns:
the number of bins.

setBins

public void setBins(int numBins)
Sets the number of bins to divide each selected numeric attribute into

Parameters:
numBins - the number of bins

invertSelectionTipText

public java.lang.String invertSelectionTipText()
Returns the tip text for this property

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

getInvertSelection

public boolean getInvertSelection()
Gets whether the supplied columns are to be removed or kept

Returns:
true if the supplied columns will be kept

setInvertSelection

public void setInvertSelection(boolean invert)
Sets whether selected columns should be removed or kept. If true the selected columns are kept and unselected columns are deleted. If false selected columns are deleted and unselected columns are kept.

Parameters:
invert - the new invert setting

attributeIndicesTipText

public java.lang.String attributeIndicesTipText()
Returns the tip text for this property

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

getAttributeIndices

public java.lang.String getAttributeIndices()
Gets the current range selection

Returns:
a string containing a comma separated list of ranges

setAttributeIndices

public void setAttributeIndices(java.lang.String rangeList)
Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

Parameters:
rangeList - a string representing the list of attributes. Since the string will typically come from a user, attributes are indexed from 1.
eg: first-3,5,6-last
Throws:
java.lang.IllegalArgumentException - if an invalid range list is supplied

setAttributeIndicesArray

public void setAttributeIndicesArray(int[] attributes)
Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

Parameters:
attributes - an array containing indexes of attributes to Discretize. Since the array will typically come from a program, attributes are indexed from 0.
Throws:
java.lang.IllegalArgumentException - if an invalid set of ranges is supplied

getCutPoints

public double[] getCutPoints(int attributeIndex)
Gets the cut points for an attribute

Parameters:
the - index (from 0) of the attribute to get the cut points of
Returns:
an array containing the cutpoints (or null if the attribute requested isn't being Discretized

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

Parameters:
argv - should contain arguments to the filter: use -h for help