weka.classifiers.rules
Class OneR

java.lang.Object
  extended by weka.classifiers.AbstractClassifier
      extended by weka.classifiers.rules.OneR
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, Classifier, Sourcable, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class OneR
extends AbstractClassifier
implements TechnicalInformationHandler, Sourcable

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:

 @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: 5928 $
Author:
Ian H. Witten (ihw@cs.waikato.ac.nz)
See Also:
Serialized Form

Constructor Summary
OneR()
           
 
Method Summary
 void buildClassifier(Instances instances)
          Generates the classifier.
 double classifyInstance(Instance inst)
          Classifies a given instance.
 Capabilities getCapabilities()
          Returns default capabilities of the classifier.
 int getMinBucketSize()
          Get the value of minBucketSize.
 java.lang.String[] getOptions()
          Gets the current settings of the OneR classifier.
 java.lang.String getRevision()
          Returns the revision string.
 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 classifier
 java.util.Enumeration listOptions()
          Returns an enumeration describing the available options..
static void main(java.lang.String[] argv)
          Main method for testing this class
 java.lang.String minBucketSizeTipText()
          Returns the tip text for this property
 weka.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 attribute
 weka.classifiers.rules.OneR.OneRRule newRule(Attribute attr, Instances data)
          Create a rule branching on this attribute.
 void setMinBucketSize(int v)
          Set the value of minBucketSize.
 void setOptions(java.lang.String[] options)
          Parses a given list of options.
 java.lang.String toSource(java.lang.String className)
          Returns a string that describes the classifier as source.
 java.lang.String toString()
          Returns a description of the classifier
 
Methods inherited from class weka.classifiers.AbstractClassifier
debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

OneR

public OneR()
Method Detail

globalInfo

public java.lang.String globalInfo()
Returns a string describing classifier

Returns:
a description suitable for displaying in the explorer/experimenter gui

getTechnicalInformation

public 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.

Specified by:
getTechnicalInformation in interface TechnicalInformationHandler
Returns:
the technical information about this class

classifyInstance

public double classifyInstance(Instance inst)
                        throws java.lang.Exception
Classifies a given instance.

Specified by:
classifyInstance in interface Classifier
Overrides:
classifyInstance in class AbstractClassifier
Parameters:
inst - the instance to be classified
Returns:
the classification of the instance
Throws:
java.lang.Exception - if an error occurred during the prediction

getCapabilities

public Capabilities getCapabilities()
Returns default capabilities of the classifier.

Specified by:
getCapabilities in interface Classifier
Specified by:
getCapabilities in interface CapabilitiesHandler
Overrides:
getCapabilities in class AbstractClassifier
Returns:
the capabilities of this classifier
See Also:
Capabilities

buildClassifier

public void buildClassifier(Instances instances)
                     throws java.lang.Exception
Generates the classifier.

Specified by:
buildClassifier in interface Classifier
Parameters:
instances - the instances to be used for building the classifier
Throws:
java.lang.Exception - if the classifier can't be built successfully

newRule

public weka.classifiers.rules.OneR.OneRRule newRule(Attribute attr,
                                                    Instances data)
                                             throws java.lang.Exception
Create a rule branching on this attribute.

Parameters:
attr - the attribute to branch on
data - the data to be used for creating the rule
Returns:
the generated rule
Throws:
java.lang.Exception - if the rule can't be built successfully

newNominalRule

public weka.classifiers.rules.OneR.OneRRule newNominalRule(Attribute attr,
                                                           Instances data,
                                                           int[] missingValueCounts)
                                                    throws java.lang.Exception
Create a rule branching on this nominal attribute.

Parameters:
attr - the attribute to branch on
data - the data to be used for creating the rule
missingValueCounts - to be filled in
Returns:
the generated rule
Throws:
java.lang.Exception - if the rule can't be built successfully

newNumericRule

public weka.classifiers.rules.OneR.OneRRule newNumericRule(Attribute attr,
                                                           Instances data,
                                                           int[] missingValueCounts)
                                                    throws java.lang.Exception
Create a rule branching on this numeric attribute

Parameters:
attr - the attribute to branch on
data - the data to be used for creating the rule
missingValueCounts - to be filled in
Returns:
the generated rule
Throws:
java.lang.Exception - if the rule can't be built successfully

listOptions

public java.util.Enumeration listOptions()
Returns an enumeration describing the available options..

Specified by:
listOptions in interface OptionHandler
Overrides:
listOptions in class AbstractClassifier
Returns:
an enumeration of all the available options.

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
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 interface OptionHandler
Overrides:
setOptions in class AbstractClassifier
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 OneR classifier.

Specified by:
getOptions in interface OptionHandler
Overrides:
getOptions in class AbstractClassifier
Returns:
an array of strings suitable for passing to setOptions

toSource

public java.lang.String toSource(java.lang.String className)
                          throws java.lang.Exception
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);
 
where the array 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.

Specified by:
toSource in interface Sourcable
Parameters:
className - the name that should be given to the source class.
Returns:
the object source described by a string
Throws:
java.lang.Exception - if the souce can't be computed

toString

public java.lang.String toString()
Returns a description of the classifier

Overrides:
toString in class java.lang.Object
Returns:
a string representation of the classifier

minBucketSizeTipText

public java.lang.String minBucketSizeTipText()
Returns the tip text for this property

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

getMinBucketSize

public int getMinBucketSize()
Get the value of minBucketSize.

Returns:
Value of minBucketSize.

setMinBucketSize

public void setMinBucketSize(int v)
Set the value of minBucketSize.

Parameters:
v - Value to assign to minBucketSize.

getRevision

public java.lang.String getRevision()
Returns the revision string.

Specified by:
getRevision in interface RevisionHandler
Overrides:
getRevision in class AbstractClassifier
Returns:
the revision

main

public static void main(java.lang.String[] argv)
Main method for testing this class

Parameters:
argv - the commandline options