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## weka.datagenerators.clusterers
Class SubspaceCluster

    java.lang.Object
      weka.datagenerators.DataGenerator
          weka.datagenerators.ClusterGenerator
              weka.datagenerators.clusterers.SubspaceCluster

All Implemented Interfaces:
  java.io.Serializable, OptionHandler, Randomizable, RevisionHandler

    public class SubspaceCluster

extends ClusterGenerator

A data generator that produces data points in hyperrectangular subspace clusters.

Valid options are:

     -h
      Prints this help.

     -o <file>
      The name of the output file, otherwise the generated data is
      printed to stdout.

     -r <name>
      The name of the relation.

     -d
      Whether to print debug informations.

     -S
      The seed for random function (default 1)

     -a <num>
      The number of attributes (default 1).

     -c
      Class Flag, if set, the cluster is listed in extra attribute.

     -b <range>
      The indices for boolean attributes.

     -m <range>
      The indices for nominal attributes.

     -P <num>
      The noise rate in percent (default 0.0).
      Can be between 0% and 30%. (Remark: The original
      algorithm only allows noise up to 10%.)

     -C <cluster-definition>
      A cluster definition of class 'SubspaceClusterDefinition'
      (definition needs to be quoted to be recognized as
      a single argument).

     Options specific to weka.datagenerators.clusterers.SubspaceClusterDefinition:

     -A <range>
      Generates randomly distributed instances in the cluster.

     -U <range>
      Generates uniformly distributed instances in the cluster.

     -G <range>
      Generates gaussian distributed instances in the cluster.

     -D <num>,<num>
      The attribute min/max (-A and -U) or mean/stddev (-G) for
      the cluster.

     -N <num>..<num>
      The range of number of instances per cluster (default 1..50).

     -I
      Uses integer instead of continuous values (default continuous).

Version:
  $Revision: 1.5 $
Author:
  Gabi Schmidberger (gabi@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
See Also:
  Serialized Form

Field Summary
`static int` | `CONTINUOUS` cluster subtype: continuous
`static int` | `GAUSSIAN` cluster type: gaussian
`static int` | `INTEGER` cluster subtype: integer
`static Tag[]` | `TAGS_CLUSTERSUBTYPE` the tags for the cluster types
`static Tag[]` | `TAGS_CLUSTERTYPE` the tags for the cluster types
`static int` | `TOTAL_UNIFORM` cluster type: total uniform
`static int` | `UNIFORM_RANDOM` cluster type: uniform/random

Constructor Summary
`SubspaceCluster()` initializes the generator, sets the number of clusters to 0, since user has to specify them explicitly

Method Summary
`java.lang.String` | `clusterDefinitionsTipText()` Returns the tip text for this property
`Instances` | `defineDataFormat()` Initializes the format for the dataset produced.
`Instance` | `generateExample()` Generate an example of the dataset.
`Instances` | `generateExamples()` Generate all examples of the dataset.
`java.lang.String` | `generateFinished()` Compiles documentation about the data generation after the generation process
`java.lang.String` | `generateStart()` Compiles documentation about the data generation before the generation process
`ClusterDefinition[]` | `getClusterDefinitions()` returns the currently set clusters
`double` | `getNoiseRate()` Gets the percentage of noise set.
`int[]` | `getNumValues()` returns array that stores the number of values for a nominal attribute.
`java.lang.String[]` | `getOptions()` Gets the current settings of the datagenerator.
`java.lang.String` | `getRevision()` Returns the revision string.
`boolean` | `getSingleModeFlag()` Gets the single mode flag.
`java.lang.String` | `globalInfo()` Returns a string describing this data generator.
`boolean` | `isBoolean(int index)` Returns true if attribute is boolean
`boolean` | `isNominal(int index)` Returns true if attribute is nominal
`java.util.Enumeration` | `listOptions()` Returns an enumeration describing the available options.
`static void` | `main(java.lang.String[] args)` Main method for testing this class.
`java.lang.String` | `noiseRateTipText()` Returns the tip text for this property
`java.lang.String` | `numAttributesTipText()` Returns the tip text for this property
`void` | `setClusterDefinitions(ClusterDefinition[] value)` sets the clusters to use
`void` | `setNoiseRate(double newNoiseRate)` Sets the percentage of noise set.
`void` | `setNumAttributes(int numAttributes)` Sets the number of attributes the dataset should have.
`void` | `setOptions(java.lang.String[] options)` Parses a list of options for this object.

Methods inherited from class weka.datagenerators.ClusterGenerator
`booleanColsTipText, classFlagTipText, getBooleanCols, getClassFlag, getNominalCols, getNumAttributes, nominalColsTipText, setBooleanCols, setBooleanIndices, setClassFlag, setNominalCols, setNominalIndices`

Methods inherited from class weka.datagenerators.DataGenerator
`debugTipText, defaultOutput, formatTipText, getDatasetFormat, getDebug, getNumExamplesAct, getOutput, getRandom, getRelationName, getSeed, makeData, outputTipText, randomTipText, relationNameTipText, seedTipText, setDatasetFormat, setDebug, setOutput, setRandom, setRelationName, setSeed`

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

Field Detail

### UNIFORM_RANDOM

    public static final int UNIFORM_RANDOM

  cluster type: uniform/random

  See Also:
    Constant Field Values

### TOTAL_UNIFORM

    public static final int TOTAL_UNIFORM

  cluster type: total uniform

  See Also:
    Constant Field Values

### GAUSSIAN

    public static final int GAUSSIAN

  cluster type: gaussian

  See Also:
    Constant Field Values

### TAGS_CLUSTERTYPE

    public static final Tag[] TAGS_CLUSTERTYPE

  the tags for the cluster types

### CONTINUOUS

    public static final int CONTINUOUS

  cluster subtype: continuous

  See Also:
    Constant Field Values

### INTEGER

    public static final int INTEGER

  cluster subtype: integer

  See Also:
    Constant Field Values

### TAGS_CLUSTERSUBTYPE

    public static final Tag[] TAGS_CLUSTERSUBTYPE

  the tags for the cluster types

Constructor Detail

### SubspaceCluster

    public SubspaceCluster()

  initializes the generator, sets the number of clusters to 0, since user has to specify them explicitly

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this data generator.

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

### listOptions

    public java.util.Enumeration listOptions()

  Returns an enumeration describing the available options.

  Specified by:
    `listOptions` in interface `OptionHandler`
  Overrides:
    `listOptions` in class `ClusterGenerator`
  Returns:
    an enumeration of all the available options

### setOptions

    public void setOptions(java.lang.String[] options)
                    throws java.lang.Exception

  Parses a list of options for this object.

  Valid options are:

       -h
        Prints this help.

       -o <file>
        The name of the output file, otherwise the generated data is
        printed to stdout.

       -r <name>
        The name of the relation.

       -d
        Whether to print debug informations.

       -S
        The seed for random function (default 1)

       -a <num>
        The number of attributes (default 1).

       -c
        Class Flag, if set, the cluster is listed in extra attribute.

       -b <range>
        The indices for boolean attributes.

       -m <range>
        The indices for nominal attributes.

       -P <num>
        The noise rate in percent (default 0.0).
        Can be between 0% and 30%. (Remark: The original
        algorithm only allows noise up to 10%.)

       -C <cluster-definition>
        A cluster definition of class 'SubspaceClusterDefinition'
        (definition needs to be quoted to be recognized as
        a single argument).

       Options specific to weka.datagenerators.clusterers.SubspaceClusterDefinition:

       -A <range>
        Generates randomly distributed instances in the cluster.

       -U <range>
        Generates uniformly distributed instances in the cluster.

       -G <range>
        Generates gaussian distributed instances in the cluster.

       -D <num>,<num>
        The attribute min/max (-A and -U) or mean/stddev (-G) for
        the cluster.

       -N <num>..<num>
        The range of number of instances per cluster (default 1..50).

       -I
        Uses integer instead of continuous values (default continuous).

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `ClusterGenerator`
  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 datagenerator.

  Specified by:
    `getOptions` in interface `OptionHandler`
  Overrides:
    `getOptions` in class `ClusterGenerator`
  Returns:
    an array of strings suitable for passing to setOptions
  See Also:
    `DataGenerator.removeBlacklist(String[])`

### setNumAttributes

    public void setNumAttributes(int numAttributes)

  Sets the number of attributes the dataset should have.

  Overrides:
    `setNumAttributes` in class `ClusterGenerator`
  Parameters:
    `numAttributes` - the new number of attributes

### numAttributesTipText

    public java.lang.String numAttributesTipText()

  Returns the tip text for this property

  Overrides:
    `numAttributesTipText` in class `ClusterGenerator`
  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### getNoiseRate

    public double getNoiseRate()

  Gets the percentage of noise set.

  Returns:
    the percentage of noise set

### setNoiseRate

    public void setNoiseRate(double newNoiseRate)

  Sets the percentage of noise set.

  Parameters:
    `newNoiseRate` - new percentage of noise

### noiseRateTipText

    public java.lang.String noiseRateTipText()

  Returns the tip text for this property

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

### getClusterDefinitions

    public ClusterDefinition[] getClusterDefinitions()

  returns the currently set clusters

  Returns:
    the currently set clusters

### setClusterDefinitions

    public void setClusterDefinitions(ClusterDefinition[] value)
                               throws java.lang.Exception

  sets the clusters to use

  Parameters:
    `value` - the clusters do use
  Throws:
    `java.lang.Exception` - if clusters are not the correct class

### clusterDefinitionsTipText

    public java.lang.String clusterDefinitionsTipText()

  Returns the tip text for this property

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

### getSingleModeFlag

    public boolean getSingleModeFlag()

  Gets the single mode flag.

  Specified by:
    `getSingleModeFlag` in class `DataGenerator`
  Returns:
    true if methode generateExample can be used.

### defineDataFormat

    public Instances defineDataFormat()
                               throws java.lang.Exception

  Initializes the format for the dataset produced.

  Overrides:
    `defineDataFormat` in class `DataGenerator`
  Returns:
    the output data format
  Throws:
    `java.lang.Exception` - data format could not be defined
  See Also:
    `DataGenerator.defaultRelationName()`

### isBoolean

    public boolean isBoolean(int index)

  Returns true if attribute is boolean

  Parameters:
    `index` - of the attribute
  Returns:
    true if the attribute is boolean

### isNominal

    public boolean isNominal(int index)

  Returns true if attribute is nominal

  Parameters:
    `index` - of the attribute
  Returns:
    true if the attribute is nominal

### getNumValues

    public int[] getNumValues()

  returns array that stores the number of values for a nominal attribute.

  Returns:
    the array that stores the number of values for a nominal attribute

### generateExample

    public Instance generateExample()
                             throws java.lang.Exception

  Generate an example of the dataset.

  Specified by:
    `generateExample` in class `DataGenerator`
  Returns:
    the instance generated
  Throws:
    `java.lang.Exception` - if format not defined or generating
    examples one by one is not possible, because voting is chosen

### generateExamples

    public Instances generateExamples()
                               throws java.lang.Exception

  Generate all examples of the dataset.

  Specified by:
    `generateExamples` in class `DataGenerator`
  Returns:
    the instance generated
  Throws:
    `java.lang.Exception` - if format not defined

### generateFinished

    public java.lang.String generateFinished()
                                      throws java.lang.Exception

  Compiles documentation about the data generation after the generation process

  Specified by:
    `generateFinished` in class `DataGenerator`
  Returns:
    string with additional information about generated dataset
  Throws:
    `java.lang.Exception` - no input structure has been defined

### generateStart

    public java.lang.String generateStart()

  Compiles documentation about the data generation before the generation process

  Specified by:
    `generateStart` in class `DataGenerator`
  Returns:
    string with additional information

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Returns:
    the revision

### main

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

  Main method for testing this class.

  Parameters:
    `args` - should contain arguments for the data producer:

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