Discretize (weka-stable 3.6.8 API)

java.lang.Object
- weka.filters.Filter
- - weka.filters.unsupervised.attribute.PotentialClassIgnorer
  - - weka.filters.unsupervised.attribute.Discretize

All Implemented Interfaces:: Serializable, CapabilitiesHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler, UnsupervisedFilter

Direct Known Subclasses:: PKIDiscretize

public class Discretize
extends PotentialClassIgnorer
implements UnsupervisedFilter, WeightedInstancesHandler

An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. Discretization is by simple binning. Skips the class attribute if set.

Valid options are:

 -unset-class-temporarily
  Unsets the class index temporarily before the filter is
  applied to the data.
  (default: no)

 -B <num>
  Specifies the (maximum) number of bins to divide numeric attributes into.
  (default = 10)

 -M <num>
  Specifies the desired weight of instances per bin for
  equal-frequency binning. If this is set to a positive
  number then the -B option will be ignored.
  (default = -1)

 -F
  Use equal-frequency instead of equal-width discretization.

 -O
  Optimize number of bins using leave-one-out estimate
  of estimated entropy (for equal-width discretization).
  If this is set then the -B option will be ignored.

 -R <col1,col2-col4,...>
  Specifies list of columns to Discretize. First and last are valid indexes.
  (default: first-last)

 -V
  Invert matching sense of column indexes.

 -D
  Output binary attributes for discretized attributes.

Version:: $Revision: 8284 $
Author:: Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`protected double[][]`	`m_CutPoints` Store the current cutpoints
`protected String`	`m_DefaultCols` The default columns to discretize
`protected double`	`m_DesiredWeightOfInstancesPerInterval` The desired weight of instances per bin
`protected Range`	`m_DiscretizeCols` Stores which columns to Discretize
`protected boolean`	`m_FindNumBins` Find the number of bins using cross-validated entropy.
`protected boolean`	`m_MakeBinary` Output binary attributes for discretized attributes.
`protected int`	`m_NumBins` The number of bins to divide the attribute into
`protected boolean`	`m_UseEqualFrequency` Use equal-frequency binning if unsupervised discretization turned on

Fields inherited from class weka.filters.unsupervised.attribute.PotentialClassIgnorer
m_ClassIndex, m_IgnoreClass

Fields inherited from class weka.filters.Filter
m_FirstBatchDone, m_InputRelAtts, m_InputStringAtts, m_NewBatch, m_OutputRelAtts, m_OutputStringAtts

Constructor Summary

Constructors
Constructor and Description

Discretize()
Constructor - initialises the filter

Discretize(String cols)
Another constructor, sets the attribute indices immediately

Constructors
Constructor and Description
`Discretize()` Constructor - initialises the filter
`Discretize(String cols)` Another constructor, sets the attribute indices immediately

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`String`	`attributeIndicesTipText()` Returns the tip text for this property
`boolean`	`batchFinished()` Signifies that this batch of input to the filter is finished.
`String`	`binsTipText()` Returns the tip text for this property
`protected void`	`calculateCutPoints()` Generate the cutpoints for each attribute
`protected void`	`calculateCutPointsByEqualFrequencyBinning(int index)` Set cutpoints for a single attribute.
`protected void`	`calculateCutPointsByEqualWidthBinning(int index)` Set cutpoints for a single attribute.
`protected void`	`convertInstance(Instance instance)` Convert a single instance over.
`String`	`desiredWeightOfInstancesPerIntervalTipText()` Returns the tip text for this property
`protected void`	`findNumBins(int index)` Optimizes the number of bins using leave-one-out cross-validation.
`String`	`findNumBinsTipText()` Returns the tip text for this property
`String`	`getAttributeIndices()` Gets the current range selection
`int`	`getBins()` Gets the number of bins numeric attributes will be divided into
`Capabilities`	`getCapabilities()` Returns the Capabilities of this filter.
`double[]`	`getCutPoints(int attributeIndex)` Gets the cut points for an attribute
`double`	`getDesiredWeightOfInstancesPerInterval()` Get the DesiredWeightOfInstancesPerInterval value.
`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.
`String[]`	`getOptions()` Gets the current settings of the filter.
`String`	`getRevision()` Returns the revision string.
`boolean`	`getUseEqualFrequency()` Get the value of UseEqualFrequency.
`String`	`globalInfo()` Returns a string describing this filter
`boolean`	`input(Instance instance)` Input an instance for filtering.
`String`	`invertSelectionTipText()` Returns the tip text for this property
`Enumeration`	`listOptions()` Gets an enumeration describing the available options.
`static void`	`main(String[] argv)` Main method for testing this class.
`String`	`makeBinaryTipText()` Returns the tip text for this property
`void`	`setAttributeIndices(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`	`setDesiredWeightOfInstancesPerInterval(double newDesiredNumber)` Set the DesiredWeightOfInstancesPerInterval value.
`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(String[] options)` Parses a given list of options.
`protected void`	`setOutputFormat()` Set the output format.
`void`	`setUseEqualFrequency(boolean newUseEqualFrequency)` Set the value of UseEqualFrequency.
`String`	`useEqualFrequencyTipText()` Returns the tip text for this property

Methods inherited from class weka.filters.unsupervised.attribute.PotentialClassIgnorer
getIgnoreClass, getOutputFormat, ignoreClassTipText, setIgnoreClass

Methods inherited from class weka.filters.Filter
batchFilterFile, bufferInput, copyValues, copyValues, filterFile, flushInput, getCapabilities, getInputFormat, initInputLocators, initOutputLocators, inputFormatPeek, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputFormatPeek, outputPeek, push, resetQueue, runFilter, setOutputFormat, testInputFormat, toString, useFilter, wekaStaticWrapper

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

- Field Detail
  - m_DiscretizeCols
```
protected Range m_DiscretizeCols
```
    Stores which columns to Discretize
  - m_NumBins
```
protected int m_NumBins
```
    The number of bins to divide the attribute into
  - m_DesiredWeightOfInstancesPerInterval
```
protected double m_DesiredWeightOfInstancesPerInterval
```
    The desired weight of instances per bin
  - m_CutPoints
```
protected double[][] m_CutPoints
```
    Store the current cutpoints
  - m_MakeBinary
```
protected boolean m_MakeBinary
```
    Output binary attributes for discretized attributes.
  - m_FindNumBins
```
protected boolean m_FindNumBins
```
    Find the number of bins using cross-validated entropy.
  - m_UseEqualFrequency
```
protected boolean m_UseEqualFrequency
```
    Use equal-frequency binning if unsupervised discretization turned on
  - m_DefaultCols
```
protected String m_DefaultCols
```
    The default columns to discretize
- Constructor Detail
  - Discretize
```
public Discretize()
```
    Constructor - initialises the filter
  - Discretize
```
public Discretize(String cols)
```
    Another constructor, sets the attribute indices immediately
    
    Parameters:
    
    cols - the attribute indices
- Method Detail
  - listOptions
```
public Enumeration listOptions()
```
    Gets an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class PotentialClassIgnorer
    
    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:
```
 -unset-class-temporarily
  Unsets the class index temporarily before the filter is
  applied to the data.
  (default: no)
```
```
 -B <num>
  Specifies the (maximum) number of bins to divide numeric attributes into.
  (default = 10)
```
```
 -M <num>
  Specifies the desired weight of instances per bin for
  equal-frequency binning. If this is set to a positive
  number then the -B option will be ignored.
  (default = -1)
```
```
 -F
  Use equal-frequency instead of equal-width discretization.
```
```
 -O
  Optimize number of bins using leave-one-out estimate
  of estimated entropy (for equal-width discretization).
  If this is set then the -B option will be ignored.
```
```
 -R <col1,col2-col4,...>
  Specifies list of columns to Discretize. First and last are valid indexes.
  (default: first-last)
```
```
 -V
  Invert matching sense of column indexes.
```
```
 -D
  Output binary attributes for discretized attributes.
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class PotentialClassIgnorer
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the filter.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class PotentialClassIgnorer
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns the Capabilities of this filter.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Filter
    
    Returns:
    
    the capabilities of this object
    
    See Also:
    
    Capabilities
  - setInputFormat
```
public boolean setInputFormat(Instances instanceInfo)
                       throws Exception
```
    Sets the format of the input instances.
    
    Overrides:
    
    setInputFormat in class PotentialClassIgnorer
    
    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
  - 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:
    
    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:
    
    IllegalStateException - if no input structure has been defined
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing this filter
    
    Returns:
    
    a description of the filter suitable for displaying in the explorer/experimenter gui
  - findNumBinsTipText
```
public 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 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
  - desiredWeightOfInstancesPerIntervalTipText
```
public String desiredWeightOfInstancesPerIntervalTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getDesiredWeightOfInstancesPerInterval
```
public double getDesiredWeightOfInstancesPerInterval()
```
    Get the DesiredWeightOfInstancesPerInterval value.
    
    Returns:
    
    the DesiredWeightOfInstancesPerInterval value.
  - setDesiredWeightOfInstancesPerInterval
```
public void setDesiredWeightOfInstancesPerInterval(double newDesiredNumber)
```
    Set the DesiredWeightOfInstancesPerInterval value.
    
    Parameters:
    
    newDesiredNumber - The new DesiredNumber value.
  - useEqualFrequencyTipText
```
public String useEqualFrequencyTipText()
```
    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.
  - binsTipText
```
public 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 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 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 String getAttributeIndices()
```
    Gets the current range selection
    
    Returns:
    
    a string containing a comma separated list of ranges
  - setAttributeIndices
```
public void setAttributeIndices(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:
    
    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:
    
    IllegalArgumentException - if an invalid set of ranges is supplied
  - getCutPoints
```
public double[] getCutPoints(int attributeIndex)
```
    Gets the cut points for an attribute
    
    Parameters:
    
    attributeIndex - 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 has been discretized into only one interval.)
  - calculateCutPoints
```
protected void calculateCutPoints()
```
    Generate the cutpoints for each attribute
  - calculateCutPointsByEqualWidthBinning
```
protected void calculateCutPointsByEqualWidthBinning(int index)
```
    Set cutpoints for a single attribute.
    
    Parameters:
    
    index - the index of the attribute to set cutpoints for
  - calculateCutPointsByEqualFrequencyBinning
```
protected void calculateCutPointsByEqualFrequencyBinning(int index)
```
    Set cutpoints for a single attribute.
    
    Parameters:
    
    index - the index of the attribute to set cutpoints for
  - findNumBins
```
protected void findNumBins(int index)
```
    Optimizes the number of bins using leave-one-out cross-validation.
    
    Parameters:
    
    index - the attribute index
  - setOutputFormat
```
protected void setOutputFormat()
```
    Set the output format. Takes the currently defined cutpoints and m_InputFormat and calls setOutputFormat(Instances) appropriately.
  - convertInstance
```
protected void convertInstance(Instance instance)
```
    Convert a single instance over. The converted instance is added to the end of the output queue.
    
    Parameters:
    
    instance - the instance to convert
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Filter
    
    Returns:
    
    the revision
  - main
```
public static void main(String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain arguments to the filter: use -h for help

Class Discretize

Field Summary

Fields inherited from class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Fields inherited from class weka.filters.Filter

Constructor Summary

Method Summary

Methods inherited from class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Methods inherited from class weka.filters.Filter

Methods inherited from class java.lang.Object

Field Detail

m_DiscretizeCols

m_NumBins

m_DesiredWeightOfInstancesPerInterval

m_CutPoints

m_MakeBinary

m_FindNumBins

m_UseEqualFrequency

m_DefaultCols

Constructor Detail

Discretize

Discretize

Method Detail

listOptions

setOptions

getOptions

getCapabilities

setInputFormat

input

batchFinished

globalInfo

findNumBinsTipText

getFindNumBins

setFindNumBins

makeBinaryTipText

getMakeBinary

setMakeBinary

desiredWeightOfInstancesPerIntervalTipText

getDesiredWeightOfInstancesPerInterval

setDesiredWeightOfInstancesPerInterval

useEqualFrequencyTipText

getUseEqualFrequency

setUseEqualFrequency

binsTipText

getBins

setBins

invertSelectionTipText

getInvertSelection

setInvertSelection

attributeIndicesTipText

getAttributeIndices

setAttributeIndices

setAttributeIndicesArray

getCutPoints

calculateCutPoints

calculateCutPointsByEqualWidthBinning

calculateCutPointsByEqualFrequencyBinning

findNumBins

setOutputFormat

convertInstance

getRevision

main