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## weka.filters.supervised.attribute
Class Discretize

    java.lang.Object
      weka.filters.Filter
          weka.filters.supervised.attribute.Discretize

All Implemented Interfaces:
  java.io.Serializable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler, SupervisedFilter

    public class Discretize

extends Filter
implements SupervisedFilter, OptionHandler, WeightedInstancesHandler, TechnicalInformationHandler

An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes. Discretization is by Fayyad & Irani's MDL method (the default).
For more information, see:
Usama M. Fayyad, Keki B. Irani: Multi-interval discretization of continuousvalued attributes for classification learning. In: Thirteenth International Joint Conference on Articial Intelligence, 1022-1027, 1993.
Igor Kononenko: On Biases in Estimating Multi-Valued Attributes. In: 14th International Joint Conference on Articial Intelligence, 1034-1040, 1995.

BibTeX:

     @inproceedings{Fayyad1993,
        author = {Usama M. Fayyad and Keki B. Irani},
        booktitle = {Thirteenth International Joint Conference on Articial Intelligence},
        pages = {1022-1027},
        publisher = {Morgan Kaufmann Publishers},
        title = {Multi-interval discretization of continuousvalued attributes for classification learning},
        volume = {2},
        year = {1993}
     }

     @inproceedings{Kononenko1995,
        author = {Igor Kononenko},
        booktitle = {14th International Joint Conference on Articial Intelligence},
        pages = {1034-1040},
        title = {On Biases in Estimating Multi-Valued Attributes},
        year = {1995},
        PS = {http://ai.fri.uni-lj.si/papers/kononenko95-ijcai.ps.gz}
     }

Valid options are:

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

     -V
      Invert matching sense of column indexes.

     -D
      Output binary attributes for discretized attributes.

     -E
      Use better encoding of split point for MDL.

     -K
      Use Kononenko's MDL criterion.

Version:
  $Revision: 8278 $
Author:
  Len Trigg (trigg@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`Discretize()` 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` | `getAttributeIndices()` Gets the current range selection
`Capabilities` | `getCapabilities()` Returns the Capabilities of this filter.
`double[]` | `getCutPoints(int attributeIndex)` Gets the cut points for an attribute
`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.
`java.lang.String` | `getRevision()` Returns the revision string.
`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` | `getUseBetterEncoding()` Gets whether better encoding is to be used for MDL.
`boolean` | `getUseKononenko()` Gets whether Kononenko's MDL criterion is to be used.
`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).
`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 a given list of options.
`void` | `setUseBetterEncoding(boolean useBetterEncoding)` Sets whether better encoding is to be used for MDL.
`void` | `setUseKononenko(boolean useKon)` Sets whether Kononenko's MDL criterion is to be used.
`java.lang.String` | `useBetterEncodingTipText()` Returns the tip text for this property
`java.lang.String` | `useKononenkoTipText()` Returns the tip text for this property

Methods inherited from class weka.filters.Filter
`batchFilterFile, filterFile, getCapabilities, getOutputFormat, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, numPendingOutput, output, outputPeek, toString, useFilter, wekaStaticWrapper`

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

Constructor Detail

### Discretize

    public Discretize()

  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 a given list of options.

  Valid options are:

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

       -V
        Invert matching sense of column indexes.

       -D
        Output binary attributes for discretized attributes.

       -E
        Use better encoding of split point for MDL.

       -K
        Use Kononenko'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

### 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 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

### getTechnicalInformation

    public 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 `TechnicalInformationHandler`
  Returns:
    the technical information about this class

### 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

### 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

### 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.

### 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:
    `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 isn't being Discretized

### getRevision

    public java.lang.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(java.lang.String[] argv)

  Main method for testing this class.

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

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