java.lang.Object
- weka.datagenerators.DataGenerator
- - weka.datagenerators.ClassificationGenerator
  - - weka.datagenerators.classifiers.classification.RandomRBF

All Implemented Interfaces:

java.io.Serializable, OptionHandler, Randomizable, RevisionHandler
```
public class RandomRBF
extends ClassificationGenerator
```
RandomRBF data is generated by first creating a random set of centers for each class. Each center is randomly assigned a weight, a central point per attribute, and a standard deviation. To generate new instances, a center is chosen at random taking the weights of each center into consideration. Attribute values are randomly generated and offset from the center, where the overall vector has been scaled so that its length equals a value sampled randomly from the Gaussian distribution of the center. The particular center chosen determines the class of the instance.
RandomRBF data contains only numeric attributes as it is non-trivial to include nominal values.
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)
```
```
 -n <num>
  The number of examples to generate (default 100)
```
```
 -a <num>
  The number of attributes (default 10).
```
```
 -c <num>
  The number of classes (default 2)
```
```
 -C <num>
  The number of centroids to use. (default 50)
```
Version:

$Revision: 1.4 $

Author:

Richard Kirkby (rkirkby at cs dot waikato dot ac dot nz), FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor Description

RandomRBF()
initializes the generator with default values

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`Instances`	`defineDataFormat()`	Initializes the format for the dataset produced.
`Instance`	`generateExample()`	Generates one example of the dataset.
`Instances`	`generateExamples()`	Generates all examples of the dataset.
`java.lang.String`	`generateFinished()`	Generates a comment string that documentats the data generator.
`java.lang.String`	`generateStart()`	Generates a comment string that documentates the data generator.
`int`	`getNumAttributes()`	Gets the number of attributes that should be produced.
`int`	`getNumCentroids()`	Gets the number of centroids.
`int`	`getNumClasses()`	Gets the number of classes the dataset should have.
`java.lang.String[]`	`getOptions()`	Gets the current settings of the datagenerator.
`java.lang.String`	`getRevision()`	Returns the revision string.
`boolean`	`getSingleModeFlag()`	Return if single mode is set for the given data generator mode depends on option setting and or generator type.
`java.lang.String`	`globalInfo()`	Returns a string describing this data generator.
`java.util.Enumeration`	`listOptions()`	Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] args)`	Main method for executing this class.
`java.lang.String`	`numAttributesTipText()`	Returns the tip text for this property
`java.lang.String`	`numCentroidsTipText()`	Returns the tip text for this property
`java.lang.String`	`numClassesTipText()`	Returns the tip text for this property
`void`	`setNumAttributes(int numAttributes)`	Sets the number of attributes the dataset should have.
`void`	`setNumCentroids(int value)`	Sets the number of centroids to use.
`void`	`setNumClasses(int numClasses)`	Sets the number of classes the dataset should have.
`void`	`setOptions(java.lang.String[] options)`	Parses a list of options for this object.

Methods inherited from class weka.datagenerators.ClassificationGenerator
getNumExamples, numExamplesTipText, setNumExamples

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

- Constructor Detail
  - RandomRBF
```
public RandomRBF()
```
    initializes the generator with default values
- 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 ClassificationGenerator
    
    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)
    
    -n <num> The number of examples to generate (default 100)
    
    -a <num> The number of attributes (default 10).
    
    -c <num> The number of classes (default 2)
    
    -C <num> The number of centroids to use. (default 50)
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class ClassificationGenerator
    
    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 ClassificationGenerator
    
    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.
    
    Parameters:
    
    numAttributes - the new number of attributes
  - getNumAttributes
```
public int getNumAttributes()
```
    Gets the number of attributes that should be produced.
    
    Returns:
    
    the number of attributes that should be produced
  - numAttributesTipText
```
public java.lang.String numAttributesTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setNumClasses
```
public void setNumClasses(int numClasses)
```
    Sets the number of classes the dataset should have.
    
    Parameters:
    
    numClasses - the new number of classes
  - getNumClasses
```
public int getNumClasses()
```
    Gets the number of classes the dataset should have.
    
    Returns:
    
    the number of classes the dataset should have
  - numClassesTipText
```
public java.lang.String numClassesTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getNumCentroids
```
public int getNumCentroids()
```
    Gets the number of centroids.
    
    Returns:
    
    the number of centroids.
  - setNumCentroids
```
public void setNumCentroids(int value)
```
    Sets the number of centroids to use.
    
    Parameters:
    
    value - the number of centroids to use.
  - numCentroidsTipText
```
public java.lang.String numCentroidsTipText()
```
    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()
                          throws java.lang.Exception
```
    Return if single mode is set for the given data generator mode depends on option setting and or generator type.
    
    Specified by:
    
    getSingleModeFlag in class DataGenerator
    
    Returns:
    
    single mode flag
    
    Throws:
    
    java.lang.Exception - if mode is not set yet
  - defineDataFormat
```
public Instances defineDataFormat()
                           throws java.lang.Exception
```
    Initializes the format for the dataset produced. Must be called before the generateExample or generateExamples methods are used. Re-initializes the random number generator with the given seed.
    
    Overrides:
    
    defineDataFormat in class DataGenerator
    
    Returns:
    
    the format for the dataset
    
    Throws:
    
    java.lang.Exception - if the generating of the format failed
    
    See Also:
    
    DataGenerator.getSeed()
  - generateExample
```
public Instance generateExample()
                         throws java.lang.Exception
```
    Generates one example of the dataset.
    
    Specified by:
    
    generateExample in class DataGenerator
    
    Returns:
    
    the generated example
    
    Throws:
    
    java.lang.Exception - if the format of the dataset is not yet defined
    
    java.lang.Exception - if the generator only works with generateExamples which means in non single mode
  - generateExamples
```
public Instances generateExamples()
                           throws java.lang.Exception
```
    Generates all examples of the dataset. Re-initializes the random number generator with the given seed, before generating instances.
    
    Specified by:
    
    generateExamples in class DataGenerator
    
    Returns:
    
    the generated dataset
    
    Throws:
    
    java.lang.Exception - if the format of the dataset is not yet defined
    
    java.lang.Exception - if the generator only works with generateExample, which means in single mode
    
    See Also:
    
    DataGenerator.getSeed()
  - generateStart
```
public java.lang.String generateStart()
```
    Generates a comment string that documentates the data generator. By default this string is added at the beginning of the produced output as ARFF file type, next after the options.
    
    Specified by:
    
    generateStart in class DataGenerator
    
    Returns:
    
    string contains info about the generated rules
  - generateFinished
```
public java.lang.String generateFinished()
                                  throws java.lang.Exception
```
    Generates a comment string that documentats the data generator. By default this string is added at the end of theproduces output as ARFF file type.
    
    Specified by:
    
    generateFinished in class DataGenerator
    
    Returns:
    
    string contains info about the generated rules
    
    Throws:
    
    java.lang.Exception - if the generating of the documentaion fails
  - 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 executing this class.
    
    Parameters:
    
    args - should contain arguments for the data producer:

Class RandomRBF

Constructor Summary

Method Summary

Methods inherited from class weka.datagenerators.ClassificationGenerator

Methods inherited from class weka.datagenerators.DataGenerator

Methods inherited from class java.lang.Object

Constructor Detail

RandomRBF

Method Detail

globalInfo

listOptions

setOptions

getOptions

setNumAttributes

getNumAttributes

numAttributesTipText

setNumClasses

getNumClasses

numClassesTipText

getNumCentroids

setNumCentroids

numCentroidsTipText

getSingleModeFlag

defineDataFormat

generateExample

generateExamples

generateStart

generateFinished

getRevision

main