weka.datagenerators.classifiers.regression

Class Expression

java.lang.Object

weka.datagenerators.DataGenerator

weka.datagenerators.RegressionGenerator

weka.datagenerators.classifiers.regression.MexicanHat

weka.datagenerators.classifiers.regression.Expression

All Implemented Interfaces:

Serializable, OptionHandler, Randomizable, RevisionHandler

public class Expression
extends MexicanHat

A data generator for generating y according to a given expression out of randomly generated x.
E.g., the mexican hat can be generated like this:
sin(abs(a1)) / abs(a1)
In addition to this function, the amplitude can be changed and gaussian noise can be added.

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 amplitude multiplier (default 1.0).

 -R <num>..<num>
  The range x is randomly drawn from (default -10.0..10.0).

 -N <num>
  The noise rate (default 0.0).

 -V <num>
  The noise variance (default 1.0).

 -E <expression>
  The expression to use for generating y out of x 
  (default sin(abs(a1)) / abs(a1)).

Version:

$Revision: 1.5 $

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

AddExpression, MexicanHat, Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected String	m_Expression the expression for computing y
protected AddExpression	m_Filter the filter for generating y out of x
protected Instances	m_RawData the input data structure for the filter

Fields inherited from class weka.datagenerators.classifiers.regression.MexicanHat

m_Amplitude, m_MaxRange, m_MinRange, m_NoiseRandom, m_NoiseRate, m_NoiseVariance

Fields inherited from class weka.datagenerators.RegressionGenerator

m_NumExamples

Fields inherited from class weka.datagenerators.DataGenerator

m_CreatingRelationName, m_DatasetFormat, m_Debug, m_DefaultOutput, m_NumExamplesAct, m_OptionBlacklist, m_Output, m_Random, m_RelationName, m_Seed

Constructor Summary

Constructors

Constructor and Description
Expression() initializes the generator

Method Summary

Modifier and Type	Method and Description
String	amplitudeTipText() Returns the tip text for this property
protected String	defaultExpression() returns the default expression
Instances	defineDataFormat() Initializes the format for the dataset produced.
String	expressionTipText() Returns the tip text for this property
Instance	generateExample() Generates one example of the dataset.
Instances	generateExamples() Generates all examples of the dataset.
String	generateFinished() Generates a comment string that documentats the data generator.
String	generateStart() Generates a comment string that documentates the data generator.
String	getExpression() Gets the mathematical expression for generating y out of x
String[]	getOptions() Gets the current settings of the datagenerator BIRCHCluster.
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.
String	globalInfo() Returns a string describing this data generator.
Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(String[] args) Main method for testing this class.
void	setExpression(String value) Sets the mathematical expression to generate y out of x.
void	setOptions(String[] options) Parses a list of options for this object.

Methods inherited from class weka.datagenerators.classifiers.regression.MexicanHat

defaultAmplitude, defaultMaxRange, defaultMinRange, defaultNoiseRate, defaultNoiseVariance, getAmplitude, getMaxRange, getMinRange, getNoiseRate, getNoiseVariance, getRange, maxRangeTipText, minRangeTipText, noiseRateTipText, noiseVarianceTipText, rangeTipText, setAmplitude, setMaxRange, setMinRange, setNoiseRate, setNoiseVariance, setRange

Methods inherited from class weka.datagenerators.RegressionGenerator

defaultNumExamples, getNumExamples, numExamplesTipText, setNumExamples

Methods inherited from class weka.datagenerators.DataGenerator

addToBlacklist, clearBlacklist, debugTipText, defaultNumExamplesAct, defaultOutput, defaultRelationName, defaultSeed, enumToVector, formatTipText, getDatasetFormat, getDebug, getNumExamplesAct, getOutput, getRandom, getRelationName, getRelationNameToUse, getSeed, isOnBlacklist, makeData, makeOptionString, numExamplesActTipText, outputTipText, randomTipText, relationNameTipText, removeBlacklist, runDataGenerator, seedTipText, setDatasetFormat, setDebug, setNumExamplesAct, setOutput, setRandom, setRelationName, setSeed, toStringFormat

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

m_Expression

protected String m_Expression

the expression for computing y

m_Filter

protected AddExpression m_Filter

the filter for generating y out of x

m_RawData

protected Instances m_RawData

the input data structure for the filter

Constructor Detail

Expression

public Expression()

initializes the generator

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this data generator.

Overrides:

globalInfo in class MexicanHat

Returns:

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

listOptions

public Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class MexicanHat

Returns:

an enumeration of all the available options

setOptions

public void setOptions(String[] options)
                throws 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 amplitude multiplier (default 1.0).

 -R <num>..<num>
  The range x is randomly drawn from (default -10.0..10.0).

 -N <num>
  The noise rate (default 0.0).

 -V <num>
  The noise variance (default 1.0).

 -E <expression>
  The expression to use for generating y out of x 
  (default sin(abs(a1)) / abs(a1)).

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class MexicanHat

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 datagenerator BIRCHCluster.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class MexicanHat

Returns:

an array of strings suitable for passing to setOptions

See Also:

DataGenerator.removeBlacklist(String[])

amplitudeTipText

public String amplitudeTipText()

Returns the tip text for this property

Overrides:

amplitudeTipText in class MexicanHat

Returns:

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

defaultExpression

protected String defaultExpression()

returns the default expression

Returns:

the default expression

getExpression

public String getExpression()

Gets the mathematical expression for generating y out of x

Returns:

the expression for computing y

setExpression

public void setExpression(String value)

Sets the mathematical expression to generate y out of x.

Parameters:

value - the expression for computing y

expressionTipText

public String expressionTipText()

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 Exception

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

Overrides:

getSingleModeFlag in class MexicanHat

Returns:

single mode flag

Throws:

Exception - if mode is not set yet

defineDataFormat

public Instances defineDataFormat()
                           throws 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 MexicanHat

Returns:

the format for the dataset

Throws:

Exception - if the generating of the format failed

See Also:

DataGenerator.getSeed()

generateExample

public Instance generateExample()
                         throws Exception

Generates one example of the dataset.

Overrides:

generateExample in class MexicanHat

Returns:

the generated example

Throws:

Exception - if the format of the dataset is not yet defined

Exception - if the generator only works with generateExamples which means in non single mode

generateExamples

public Instances generateExamples()
                           throws Exception

Generates all examples of the dataset. Re-initializes the random number generator with the given seed, before generating instances.

Overrides:

generateExamples in class MexicanHat

Returns:

the generated dataset

Throws:

Exception - if the format of the dataset is not yet defined

Exception - if the generator only works with generateExample, which means in single mode

See Also:

DataGenerator.getSeed()

generateStart

public 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.

Overrides:

generateStart in class MexicanHat

Returns:

string contains info about the generated rules

generateFinished

public String generateFinished()
                        throws 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.

Overrides:

generateFinished in class MexicanHat

Returns:

string contains info about the generated rules

Throws:

Exception - if the generating of the documentaion fails

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class MexicanHat

Returns:

the revision

main

public static void main(String[] args)

Main method for testing this class.

Parameters:

args - should contain arguments for the data producer: