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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.meta.OrdinalClassClassifier
public class OrdinalClassClassifier
Meta classifier that allows standard classification algorithms to be applied to ordinal class problems.
For more information see:
Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. In: 12th European Conference on Machine Learning, 145-156, 2001.
@inproceedings{Frank2001,
author = {Eibe Frank and Mark Hall},
booktitle = {12th European Conference on Machine Learning},
pages = {145-156},
publisher = {Springer},
title = {A Simple Approach to Ordinal Classification},
year = {2001}
}
Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
OptionHandler,
Serialized Form| Constructor Summary | |
|---|---|
OrdinalClassClassifier()
Default constructor. |
|
| Method Summary | |
|---|---|
void |
buildClassifier(Instances insts)
Builds the classifiers. |
double[] |
distributionForInstance(Instance inst)
Returns the distribution for an instance. |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
java.lang.String[] |
getOptions()
Gets the current settings of the 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 this attribute evaluator |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
java.lang.String |
toString()
Prints the classifiers. |
| Methods inherited from class weka.classifiers.SingleClassifierEnhancer |
|---|
classifierTipText, getClassifier, setClassifier |
| Methods inherited from class weka.classifiers.Classifier |
|---|
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
|---|
public OrdinalClassClassifier()
| Method Detail |
|---|
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic Capabilities getCapabilities()
getCapabilities in interface CapabilitiesHandlergetCapabilities in class SingleClassifierEnhancerCapabilities
public void buildClassifier(Instances insts)
throws java.lang.Exception
buildClassifier in class Classifierinsts - the training data.
java.lang.Exception - if a classifier can't be built
public double[] distributionForInstance(Instance inst)
throws java.lang.Exception
distributionForInstance in class Classifierinst - the instance to compute the distribution for
java.lang.Exception - if the distribution can't be computed successfullypublic java.util.Enumeration listOptions()
listOptions in interface OptionHandlerlistOptions in class SingleClassifierEnhancer
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
setOptions in interface OptionHandlersetOptions in class SingleClassifierEnhanceroptions - 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 OptionHandlergetOptions in class SingleClassifierEnhancerpublic java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class Classifierpublic static void main(java.lang.String[] argv)
argv - the options
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