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Class weka.filters.DiscretizeFilter

java.lang.Object
   |
   +----weka.filters.Filter
           |
           +----weka.filters.DiscretizeFilter

public class DiscretizeFilter

extends Filter

implements OptionHandler, WeightedInstancesHandler

Valid filter-specific options are:

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

-O
Optimizes the number of bins using a leave-one-out estimate of the entropy.

-R col1,col2-col4,...
Specify 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: 1.5 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz) (Fayyad and Irani's method)

DiscretizeFilter()

Constructor - initialises the filter

batchFinished()

Signifies that this batch of input to the filter is finished.

getAttributeIndices()

Gets the current range selection

getBins()

Gets the number of bins numeric attributes will be divided into

getCutPoints(int)

Gets the cut points for an attribute

getFindNumBins()

Get the value of FindNumBins.

getInvertSelection()

Gets whether the supplied columns are to be removed or kept

getMakeBinary()

Gets whether binary attributes should be made for discretized ones.

getOptimzeBinning()

Get if binning is to be optimized.

getOptions()

Gets the current settings of the filter.

getUseBetterEncoding()

Gets whether better encoding is to be used for MDL.

getUseKononenko()

Gets whether Kononenko's MDL criterion is to be used.

getUseMDL()

Gets whether MDL will be used as the discretisation method

input(Instance)

Input an instance for filtering.

inputFormat(Instances)

Sets the format of the input instances.

listOptions()

Gets an enumeration describing the available options

main(String[])

Main method for testing this class.

setAttributeIndices(String)

Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

setAttributeIndicesArray(int[])

Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

setBins(int)

Sets the number of bins to divide each selected numeric attribute into

setFindNumBins(boolean)

Set the value of FindNumBins.

setInvertSelection(boolean)

Sets whether selected columns should be removed or kept.

setMakeBinary(boolean)

Sets whether binary attributes should be made for discretized ones.

setOptimizeBinning(boolean)

Sets if binning is to be optimized.

setOptions(String[])

Parses the options for this object.

setUseBetterEncoding(boolean)

Sets whether better encoding is to be used for MDL.

setUseKononenko(boolean)

Sets whether Kononenko's MDL criterion is to be used.

setUseMDL(boolean)

Sets whether MDL will be used as the discretisation method

 public DiscretizeFilter()

Constructor - initialises the filter

 public Enumeration listOptions()

Gets an enumeration describing the available options

Returns:

an enumeration of all the available options

 public void setOptions(String options[]) throws Exception

Parses the options for this object. Valid options are:

-B num
Specify the (maximum) number of equal-width bins to divide numeric attributes into. (default class-based discretization).

-O Optimizes the number of bins using a leave-one-out estimate of the entropy. -R col1,col2-col4,...
Specify 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.

Parameters:

options - the list of options as an array of strings

Throws: Exception

if an option is not supported

 public String[] getOptions()

Gets the current settings of the filter.

Returns:

an array of strings suitable for passing to setOptions

 public boolean inputFormat(Instances instanceInfo) throws Exception

Sets the format of the input instances.

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: Exception

if the input format can't be set successfully

Overrides:

inputFormat in class Filter

 public boolean input(Instance instance) throws Exception

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.

Parameters:

instance - the input instance

Returns:

true if the filtered instance may now be collected with output().

Throws: Exception

if the input instance was not of the correct format or if there was a problem with the filtering.

Overrides:

input in class Filter

 public boolean batchFinished() throws Exception

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.

Returns:

true if there are instances pending output

Throws: Exception

if no input structure has been defined

Overrides:

batchFinished in class Filter

 public boolean getFindNumBins()

Get the value of FindNumBins.

Returns:

Value of FindNumBins.

 public void setFindNumBins(boolean newFindNumBins)

Set the value of FindNumBins.

Parameters:

newFindNumBins - Value to assign to FindNumBins.

 public boolean getMakeBinary()

Gets whether binary attributes should be made for discretized ones.

Returns:

true if attributes will be binarized

 public void setMakeBinary(boolean makeBinary)

Sets whether binary attributes should be made for discretized ones.

Parameters:

makeBinary - if binary attributes are to be made

 public boolean getUseMDL()

Gets whether MDL will be used as the discretisation method

Returns:

true if so

 public void setUseMDL(boolean useMDL)

Sets whether MDL will be used as the discretisation method

Parameters:

useMDL - true if MDL should be used

 public boolean getUseKononenko()

Gets whether Kononenko's MDL criterion is to be used.

Returns:

true if Kononenko's criterion will be used.

 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

 public boolean getUseBetterEncoding()

Gets whether better encoding is to be used for MDL.

Returns:

true if the better MDL encoding will be used

 public void setUseBetterEncoding(boolean useBetterEncoding)

Sets whether better encoding is to be used for MDL.

Parameters:

useBetterEncoding - true if better encoding to be used.

 public int getBins()

Gets the number of bins numeric attributes will be divided into

Returns:

the number of bins.

 public void setBins(int numBins)

Sets the number of bins to divide each selected numeric attribute into

Parameters:

numBins - the number of bins

 public boolean getInvertSelection()

Gets whether the supplied columns are to be removed or kept

Returns:

true if the supplied columns will be kept

 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

 public String getAttributeIndices()

Gets the current range selection

Returns:

a string containing a comma separated list of ranges

 public void setAttributeIndices(String rangeList) throws Exception

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: Exception

if an invalid range list is supplied

 public void setAttributeIndicesArray(int attributes[]) throws Exception

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: Exception

if an invalid set of ranges is supplied

 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

 public boolean getOptimzeBinning()

Get if binning is to be optimized.

Returns:

if binning is to be optimized

 public void setOptimizeBinning(boolean bool)

Sets if binning is to be optimized.

Parameters:

bool - set if binning

 public static void main(String argv[])

Main method for testing this class.

Parameters:

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

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