public class NaiveBayesMultinomial extends AbstractClassifier implements WeightedInstancesHandler, TechnicalInformationHandler
@inproceedings{Mccallum1998,
author = {Andrew Mccallum and Kamal Nigam},
booktitle = {AAAI-98 Workshop on 'Learning for Text Categorization'},
title = {A Comparison of Event Models for Naive Bayes Text Classification},
year = {1998}
}
Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT| Constructor and Description |
|---|
NaiveBayesMultinomial() |
| Modifier and Type | Method and Description |
|---|---|
void |
buildClassifier(Instances instances)
Generates the classifier.
|
double[] |
distributionForInstance(Instance instance)
Calculates the class membership probabilities for the given test
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 this classifier
|
double |
lnFactorial(int n)
Fast computation of ln(n!) for non-negative ints
negative ints are passed on to the general gamma-function
based version in weka.core.SpecialFunctions
if the current n value is higher than any previous one,
the cache is extended and filled to cover it
the common case is reduced to a simple array lookup
|
static void |
main(java.lang.String[] argv)
Main method for testing this class.
|
java.lang.String |
toString()
Returns a string representation of the classifier.
|
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getOptions, implementsMoreEfficientBatchPrediction, listOptions, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces, setOptionspublic java.lang.String globalInfo()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation in interface TechnicalInformationHandlerpublic Capabilities getCapabilities()
getCapabilities in interface ClassifiergetCapabilities in interface CapabilitiesHandlergetCapabilities in class AbstractClassifierCapabilitiespublic void buildClassifier(Instances instances) throws java.lang.Exception
buildClassifier in interface Classifierinstances - set of instances serving as training datajava.lang.Exception - if the classifier has not been generated successfullypublic double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance in interface ClassifierdistributionForInstance in class AbstractClassifierinstance - the instance to be classifiedjava.lang.Exception - if there is a problem generating the predictionpublic double lnFactorial(int n)
n - the integerpublic 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