public class ClassificationViaRegression extends SingleClassifierEnhancer implements TechnicalInformationHandler
@article{Frank1998,
author = {E. Frank and Y. Wang and S. Inglis and G. Holmes and I.H. Witten},
journal = {Machine Learning},
number = {1},
pages = {63-76},
title = {Using model trees for classification},
volume = {32},
year = {1998}
}
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.M5P)
Options specific to classifier weka.classifiers.trees.M5P:
-N Use unpruned tree/rules
-U Use unsmoothed predictions
-R Build regression tree/rule rather than a model tree/rule
-M <minimum number of instances> Set minimum number of instances per leaf (default 4)
-L Save instances at the nodes in the tree (for visualization purposes)
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT| Constructor and Description |
|---|
ClassificationViaRegression()
Default constructor.
|
| Modifier and Type | Method and Description |
|---|---|
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 |
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
|
static void |
main(java.lang.String[] argv)
Main method for testing this class.
|
java.lang.String |
toString()
Prints the classifiers.
|
classifierTipText, getClassifier, getOptions, listOptions, postExecution, preExecution, setClassifier, setOptionsbatchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlacespublic ClassificationViaRegression()
public java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic Capabilities getCapabilities()
getCapabilities in interface ClassifiergetCapabilities in interface CapabilitiesHandlergetCapabilities in class SingleClassifierEnhancerCapabilitiespublic void buildClassifier(Instances insts) throws java.lang.Exception
buildClassifier in interface Classifierinsts - the training data.java.lang.Exception - if a classifier can't be builtpublic double[] distributionForInstance(Instance inst) throws java.lang.Exception
distributionForInstance in interface ClassifierdistributionForInstance in class AbstractClassifierinst - the instance to get the distribution forjava.lang.Exception - if the distribution can't be computed successfullypublic java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String getRevision()
getRevision in interface RevisionHandlergetRevision in class AbstractClassifierpublic static void main(java.lang.String[] argv)
argv - the options for the learner