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java.lang.Objectweka.datagenerators.DataGenerator
weka.datagenerators.ClassificationGenerator
weka.datagenerators.classifiers.classification.Agrawal
public class Agrawal
Generates a people database and is based on the paper by Agrawal et al.:
R. Agrawal, T. Imielinski, A. Swami (1993). Database Mining: A Performance Perspective. IEEE Transactions on Knowledge and Data Engineering. 5(6):914-925. URL http://www.almaden.ibm.com/software/quest/Publications/ByDate.html.
@article{Agrawal1993, author = {R. Agrawal and T. Imielinski and A. Swami}, journal = {IEEE Transactions on Knowledge and Data Engineering}, note = {Special issue on Learning and Discovery in Knowledge-Based Databases}, number = {6}, pages = {914-925}, title = {Database Mining: A Performance Perspective}, volume = {5}, year = {1993}, URL = {http://www.almaden.ibm.com/software/quest/Publications/ByDate.html}, PDF = {http://www.almaden.ibm.com/software/quest/Publications/papers/tkde93.pdf} }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)
-F <num> The function to use for generating the data. (default 1)
-B Whether to balance the class.
-P <num> The perturbation factor. (default 0.05)
Field Summary | |
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static int |
FUNCTION_1
function 1 |
static int |
FUNCTION_10
function 10 |
static int |
FUNCTION_2
function 2 |
static int |
FUNCTION_3
function 3 |
static int |
FUNCTION_4
function 4 |
static int |
FUNCTION_5
function 5 |
static int |
FUNCTION_6
function 6 |
static int |
FUNCTION_7
function 7 |
static int |
FUNCTION_8
function 8 |
static int |
FUNCTION_9
function 9 |
static Tag[] |
FUNCTION_TAGS
the funtion tags |
Constructor Summary | |
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Agrawal()
initializes the generator with default values |
Method Summary | |
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java.lang.String |
balanceClassTipText()
Returns the tip text for this property |
Instances |
defineDataFormat()
Initializes the format for the dataset produced. |
java.lang.String |
functionTipText()
Returns the tip text for this property |
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. |
boolean |
getBalanceClass()
Gets whether the class is balanced. |
SelectedTag |
getFunction()
Gets the function for generating the data. |
java.lang.String[] |
getOptions()
Gets the current settings of the datagenerator. |
double |
getPerturbationFraction()
Gets the perturbation fraction. |
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. |
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. |
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 |
perturbationFractionTipText()
Returns the tip text for this property |
void |
setBalanceClass(boolean value)
Sets whether the class is balanced. |
void |
setFunction(SelectedTag value)
Sets the function for generating the data. |
void |
setOptions(java.lang.String[] options)
Parses a list of options for this object. |
void |
setPerturbationFraction(double value)
Sets the perturbation fraction. |
Methods inherited from class weka.datagenerators.ClassificationGenerator |
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getNumExamples, numExamplesTipText, setNumExamples |
Methods inherited from class weka.datagenerators.DataGenerator |
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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 |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final int FUNCTION_1
public static final int FUNCTION_2
public static final int FUNCTION_3
public static final int FUNCTION_4
public static final int FUNCTION_5
public static final int FUNCTION_6
public static final int FUNCTION_7
public static final int FUNCTION_8
public static final int FUNCTION_9
public static final int FUNCTION_10
public static final Tag[] FUNCTION_TAGS
Constructor Detail |
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public Agrawal()
Method Detail |
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public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public java.util.Enumeration 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)
-F <num> The function to use for generating the data. (default 1)
-B Whether to balance the class.
-P <num> The perturbation factor. (default 0.05)
setOptions
in interface OptionHandler
setOptions
in class ClassificationGenerator
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class ClassificationGenerator
DataGenerator.removeBlacklist(String[])
public SelectedTag getFunction()
FUNCTION_TAGS
public void setFunction(SelectedTag value)
value
- the function.FUNCTION_TAGS
public java.lang.String functionTipText()
public boolean getBalanceClass()
public void setBalanceClass(boolean value)
value
- whether to balance the class.public java.lang.String balanceClassTipText()
public double getPerturbationFraction()
public void setPerturbationFraction(double value)
value
- the perturbation fraction.public java.lang.String perturbationFractionTipText()
public boolean getSingleModeFlag() throws java.lang.Exception
getSingleModeFlag
in class DataGenerator
java.lang.Exception
- if mode is not set yetpublic Instances defineDataFormat() throws java.lang.Exception
defineDataFormat
in class DataGenerator
java.lang.Exception
- if the generating of the format failedDataGenerator.getSeed()
public Instance generateExample() throws java.lang.Exception
generateExample
in class DataGenerator
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 modepublic Instances generateExamples() throws java.lang.Exception
generateExamples
in class DataGenerator
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 modeDataGenerator.getSeed()
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
- if the generating of the documentaion failspublic java.lang.String getRevision()
getRevision
in interface RevisionHandler
public static void main(java.lang.String[] args)
args
- should contain arguments for the data producer:
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