public class RDG1 extends ClassificationGenerator
-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)
-R <num> maximum size for rules (default 10)
-M <num> minimum size for rules (default 1)
-I <num> number of irrelevant attributes (default 0)
-N number of numeric attributes (default 0)
-V switch on voting (default is no voting)Following an example of a generated dataset:
% % weka.datagenerators.RDG1 -r expl -a 2 -c 3 -n 4 -N 1 -I 0 -M 2 -R 10 -S 2 % relation expl attribute a0 {false,true} attribute a1 numeric attribute class {c0,c1,c2} data true,0.496823,c0 false,0.743158,c1 false,0.408285,c1 false,0.993687,c2 % % Number of attributes chosen as irrelevant = 0 % % DECISIONLIST (number of rules = 3): % RULE 0: c0 := a1 < 0.986, a0 % RULE 1: c1 := a1 < 0.95, not(a0) % RULE 2: c2 := not(a0), a1 >= 0.562
Constructor and Description |
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RDG1()
initializes the generator with default values
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Modifier and Type | Method and Description |
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java.lang.String |
attList_IrrTipText()
Returns the tip text for this property
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Instances |
defineDataFormat()
Initializes the format for the dataset produced.
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Instance |
generateExample()
Generate an example of the dataset dataset.
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Instances |
generateExamples()
Generate all examples of the dataset.
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Instances |
generateExamples(int num,
java.util.Random random,
Instances format)
Generate all examples of the dataset.
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java.lang.String |
generateFinished()
Compiles documentation about the data generation.
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java.lang.String |
generateStart()
Generates a comment string that documentates the data generator.
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boolean[] |
getAttList_Irr()
Gets the array that defines which of the attributes are seen to be
irrelevant.
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int |
getMaxRuleSize()
Gets the maximum number of tests in rules.
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int |
getMinRuleSize()
Gets the minimum number of tests in rules.
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int |
getNumAttributes()
Gets the number of attributes that should be produced.
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int |
getNumClasses()
Gets the number of classes the dataset should have.
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int |
getNumIrrelevant()
Gets the number of irrelevant attributes.
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int |
getNumNumeric()
Gets the number of numerical attributes.
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java.lang.String[] |
getOptions()
Gets the current settings of the datagenerator RDG1.
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java.lang.String |
getRevision()
Returns the revision string.
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boolean |
getSingleModeFlag()
Gets the single mode flag.
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boolean |
getVoteFlag()
Gets the vote flag.
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java.lang.String |
globalInfo()
Returns a string describing this data generator.
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java.util.Enumeration<Option> |
listOptions()
Returns an enumeration describing the available options.
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static void |
main(java.lang.String[] args)
Main method for testing this class.
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java.lang.String |
maxRuleSizeTipText()
Returns the tip text for this property
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java.lang.String |
minRuleSizeTipText()
Returns the tip text for this property
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java.lang.String |
numAttributesTipText()
Returns the tip text for this property
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java.lang.String |
numClassesTipText()
Returns the tip text for this property
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java.lang.String |
numIrrelevantTipText()
Returns the tip text for this property
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java.lang.String |
numNumericTipText()
Returns the tip text for this property
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void |
setAttList_Irr(boolean[] newAttList_Irr)
Sets the array that defines which of the attributes are seen to be
irrelevant.
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void |
setMaxRuleSize(int newMaxRuleSize)
Sets the maximum number of tests in rules.
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void |
setMinRuleSize(int newMinRuleSize)
Sets the minimum number of tests in rules.
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void |
setNumAttributes(int numAttributes)
Sets the number of attributes the dataset should have.
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void |
setNumClasses(int numClasses)
Sets the number of classes the dataset should have.
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void |
setNumIrrelevant(int newNumIrrelevant)
Sets the number of irrelevant attributes.
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void |
setNumNumeric(int newNumNumeric)
Sets the number of numerical attributes.
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void |
setOptions(java.lang.String[] options)
Parses a list of options for this object.
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void |
setVoteFlag(boolean newVoteFlag)
Sets the vote flag.
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java.lang.String |
voteFlagTipText()
Returns the tip text for this property
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getNumExamples, numExamplesTipText, setNumExamples
debugTipText, defaultOutput, enumToVector, formatTipText, getDatasetFormat, getDebug, getNumExamplesAct, getOutput, getRandom, getRelationName, getSeed, makeData, outputTipText, randomTipText, relationNameTipText, runDataGenerator, seedTipText, setDatasetFormat, setDebug, setOutput, setRandom, setRelationName, setSeed
public java.lang.String globalInfo()
public java.util.Enumeration<Option> listOptions()
listOptions
in interface OptionHandler
listOptions
in class ClassificationGenerator
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-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)
-R <num> maximum size for rules (default 10)
-M <num> minimum size for rules (default 1)
-I <num> number of irrelevant attributes (default 0)
-N number of numeric attributes (default 0)
-V switch on voting (default is no voting)
setOptions
in interface OptionHandler
setOptions
in class ClassificationGenerator
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class ClassificationGenerator
DataGenerator.removeBlacklist(String[])
public void setNumAttributes(int numAttributes)
numAttributes
- the new number of attributespublic int getNumAttributes()
public java.lang.String numAttributesTipText()
public void setNumClasses(int numClasses)
numClasses
- the new number of classespublic int getNumClasses()
public java.lang.String numClassesTipText()
public int getMaxRuleSize()
public void setMaxRuleSize(int newMaxRuleSize)
newMaxRuleSize
- new maximum number of tests allowed in rules.public java.lang.String maxRuleSizeTipText()
public int getMinRuleSize()
public void setMinRuleSize(int newMinRuleSize)
newMinRuleSize
- new minimum number of test in rules.public java.lang.String minRuleSizeTipText()
public int getNumIrrelevant()
public void setNumIrrelevant(int newNumIrrelevant)
newNumIrrelevant
- the number of irrelevant attributes.public java.lang.String numIrrelevantTipText()
public int getNumNumeric()
public void setNumNumeric(int newNumNumeric)
newNumNumeric
- the number of numerical attributes.public java.lang.String numNumericTipText()
public boolean getVoteFlag()
public void setVoteFlag(boolean newVoteFlag)
newVoteFlag
- boolean with the new setting of the vote flag.public java.lang.String voteFlagTipText()
public boolean getSingleModeFlag()
getSingleModeFlag
in class DataGenerator
public boolean[] getAttList_Irr()
public void setAttList_Irr(boolean[] newAttList_Irr)
newAttList_Irr
- array that defines the irrelevant attributes.public java.lang.String attList_IrrTipText()
public Instances defineDataFormat() throws java.lang.Exception
defineDataFormat
in class DataGenerator
java.lang.Exception
- data format could not be definedDataGenerator.defaultRelationName()
public Instance generateExample() throws java.lang.Exception
generateExample
in class DataGenerator
java.lang.Exception
- if format not defined or generating public Instances generateExamples() throws java.lang.Exception
generateExamples
in class DataGenerator
java.lang.Exception
- if format not defined or generating public Instances generateExamples(int num, java.util.Random random, Instances format) throws java.lang.Exception
num
- the number of examples to generaterandom
- the random number generator to useformat
- the dataset formatjava.lang.Exception
- if format not defined or generating public java.lang.String generateStart()
generateStart
in class DataGenerator
public java.lang.String generateFinished() throws java.lang.Exception
generateFinished
in class DataGenerator
java.lang.Exception
- no input structure has been definedpublic java.lang.String getRevision()
public static void main(java.lang.String[] args)
args
- should contain arguments for the data producer: