Package weka.classifiers.rules
Class OneR
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.rules.OneR
- All Implemented Interfaces:
Serializable
,Cloneable
,Classifier
,Sourcable
,BatchPredictor
,CapabilitiesHandler
,CapabilitiesIgnorer
,CommandlineRunnable
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
Class for building and using a 1R classifier; in
other words, uses the minimum-error attribute for prediction, discretizing
numeric attributes. For more information, see:
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91. BibTeX:
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91. BibTeX:
@article{Holte1993, author = {R.C. Holte}, journal = {Machine Learning}, pages = {63-91}, title = {Very simple classification rules perform well on most commonly used datasets}, volume = {11}, year = {1993} }Valid options are:
-B <minimum bucket size> The minimum number of objects in a bucket (default: 6).
- Version:
- $Revision: 10153 $
- Author:
- Ian H. Witten (ihw@cs.waikato.ac.nz)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.AbstractClassifier
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances instances) Generates the classifier.double
classifyInstance
(Instance inst) Classifies a given instance.Returns default capabilities of the classifier.int
Get the value of minBucketSize.String[]
Gets the current settings of the OneR classifier.Returns the revision string.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.Returns a string describing classifierReturns an enumeration describing the available options..static void
Main method for testing this classReturns the tip text for this propertyweka.classifiers.rules.OneR.OneRRule
newNominalRule
(Attribute attr, Instances data, int[] missingValueCounts) Create a rule branching on this nominal attribute.weka.classifiers.rules.OneR.OneRRule
newNumericRule
(Attribute attr, Instances data, int[] missingValueCounts) Create a rule branching on this numeric attributeweka.classifiers.rules.OneR.OneRRule
Create a rule branching on this attribute.void
setMinBucketSize
(int v) Set the value of minBucketSize.void
setOptions
(String[] options) Parses a given list of options.Returns a string that describes the classifier as source.toString()
Returns a description of the classifierMethods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
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Constructor Details
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OneR
public OneR()
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Method Details
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globalInfo
Returns a string describing classifier- Returns:
- a description suitable for displaying in the explorer/experimenter gui
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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.- Specified by:
getTechnicalInformation
in interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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classifyInstance
Classifies a given instance.- Specified by:
classifyInstance
in interfaceClassifier
- Overrides:
classifyInstance
in classAbstractClassifier
- Parameters:
inst
- the instance to be classified- Returns:
- the classification of the instance
- Throws:
Exception
- if an error occurred during the prediction
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getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Specified by:
getCapabilities
in interfaceClassifier
- Overrides:
getCapabilities
in classAbstractClassifier
- Returns:
- the capabilities of this classifier
- See Also:
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buildClassifier
Generates the classifier.- Specified by:
buildClassifier
in interfaceClassifier
- Parameters:
instances
- the instances to be used for building the classifier- Throws:
Exception
- if the classifier can't be built successfully
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newRule
public weka.classifiers.rules.OneR.OneRRule newRule(Attribute attr, Instances data) throws Exception Create a rule branching on this attribute.- Parameters:
attr
- the attribute to branch ondata
- the data to be used for creating the rule- Returns:
- the generated rule
- Throws:
Exception
- if the rule can't be built successfully
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newNominalRule
public weka.classifiers.rules.OneR.OneRRule newNominalRule(Attribute attr, Instances data, int[] missingValueCounts) throws Exception Create a rule branching on this nominal attribute.- Parameters:
attr
- the attribute to branch ondata
- the data to be used for creating the rulemissingValueCounts
- to be filled in- Returns:
- the generated rule
- Throws:
Exception
- if the rule can't be built successfully
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newNumericRule
public weka.classifiers.rules.OneR.OneRRule newNumericRule(Attribute attr, Instances data, int[] missingValueCounts) throws Exception Create a rule branching on this numeric attribute- Parameters:
attr
- the attribute to branch ondata
- the data to be used for creating the rulemissingValueCounts
- to be filled in- Returns:
- the generated rule
- Throws:
Exception
- if the rule can't be built successfully
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listOptions
Returns an enumeration describing the available options..- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classAbstractClassifier
- Returns:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-B <minimum bucket size> The minimum number of objects in a bucket (default: 6).
- Specified by:
setOptions
in interfaceOptionHandler
- Overrides:
setOptions
in classAbstractClassifier
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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getOptions
Gets the current settings of the OneR classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classAbstractClassifier
- Returns:
- an array of strings suitable for passing to setOptions
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toSource
Returns a string that describes the classifier as source. The classifier will be contained in a class with the given name (there may be auxiliary classes), and will contain a method with the signature:public static double classify(Object[] i);
i
contains elements that are either Double, String, with missing values represented as null. The generated code is public domain and comes with no warranty. -
toString
Returns a description of the classifier -
minBucketSizeTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getMinBucketSize
public int getMinBucketSize()Get the value of minBucketSize.- Returns:
- Value of minBucketSize.
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setMinBucketSize
public void setMinBucketSize(int v) Set the value of minBucketSize.- Parameters:
v
- Value to assign to minBucketSize.
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getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classAbstractClassifier
- Returns:
- the revision
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main
Main method for testing this class- Parameters:
argv
- the commandline options
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