public class WARAM extends ARAMNetworkClass implements MultiLabelClassifierThreaded, weka.core.OptionHandler, weka.core.WeightedInstancesHandler, weka.classifiers.UpdateableClassifier, MultiLabelDrawable
For more information on Naive Bayes classifiers, see
George H. John and Pat Langley (1995). Estimating Continuous Distributions in Bayesian Classifiers. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence. pp. 338-345. Morgan Kaufmann, San Mateo.
Valid options are:
-K
Use kernel estimation for modelling numeric attributes rather than
a single normal distribution.
-D
Use supervised discretization to process numeric attributes.
activity_report, neuronsactivated, neuronsactivity, numClasses, numFeatures, threshold
BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT
BayesNet, Newick, NOT_DRAWABLE, TREE
Constructor and Description |
---|
WARAM() |
WARAM(int fnumFeatures,
int fnumClasses,
double fro,
double fthreshold) |
Modifier and Type | Method and Description |
---|---|
double[] |
ARAMm_Ranking2Class(double[] rankings) |
void |
buildClassifier(weka.core.Instances D)
Generates the classifier.
|
double |
classifyInstance(weka.core.Instance instance)
Classifies the given test instance.
|
String |
debugTipText()
Returns the tip text for this property
|
double[] |
distributionForInstance(weka.core.Instance instance)
Calculates the class membership probabilities for the given test
instance.
|
double[][] |
distributionForInstanceM(weka.core.Instances i) |
weka.core.Capabilities |
getCapabilities() |
boolean |
getDebug()
Get whether debugging is turned on.
|
String |
getModel()
Returns a string representation of the model.
|
String[] |
getOptions()
Gets the current settings of the classifier.
|
String |
globalInfo()
Returns a string describing this classifier
|
Map<Integer,String> |
graph()
Returns a string that describes a graph representing
the object.
|
Map<Integer,Integer> |
graphType()
Returns the type of graph representing
the object.
|
boolean |
isThreaded() |
Enumeration |
listOptions()
Returns an enumeration describing the available options.
|
static void |
main(String[] argv) |
void |
setDebug(boolean debug)
Set debugging mode.
|
void |
setOptions(String[] options)
Parses a given list of options.
|
void |
setThreaded(boolean setv) |
String |
toString()
Returns a description of the classifier.
|
void |
updateClassifier(weka.core.Instance instance)
Updates the classifier with the given instance.
|
testCapabilities
classifierTipText, defaultClassifierOptions, defaultClassifierString, getClassifier, getClassifierSpec, postExecution, preExecution, setClassifier
batchSizeTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDoNotCheckCapabilities, setNumDecimalPlaces
public WARAM(int fnumFeatures, int fnumClasses, double fro, double fthreshold)
public WARAM()
public String globalInfo()
public void buildClassifier(weka.core.Instances D) throws Exception
buildClassifier
in interface weka.classifiers.Classifier
instances
- set of instances serving as training dataException
- if the classifier has not been generated
successfullypublic void updateClassifier(weka.core.Instance instance) throws Exception
updateClassifier
in interface weka.classifiers.UpdateableClassifier
instance
- the new training instance to include in the modelException
- if the instance could not be incorporated in
the model.public double[] distributionForInstance(weka.core.Instance instance) throws Exception
distributionForInstance
in interface weka.classifiers.Classifier
distributionForInstance
in class weka.classifiers.AbstractClassifier
instance
- the instance to be classifiedException
- if there is a problem generating the predictionpublic double[] ARAMm_Ranking2Class(double[] rankings)
public double classifyInstance(weka.core.Instance instance) throws Exception
classifyInstance
in interface weka.classifiers.Classifier
classifyInstance
in class weka.classifiers.AbstractClassifier
instance
- the instance to be classifiedException
- if an error occurred during the predictionpublic Enumeration listOptions()
listOptions
in interface weka.core.OptionHandler
listOptions
in class weka.classifiers.SingleClassifierEnhancer
public void setOptions(String[] options) throws Exception
-K
Use kernel estimation for modelling numeric attributes rather than
a single normal distribution.
-D
Use supervised discretization to process numeric attributes.
setOptions
in interface weka.core.OptionHandler
setOptions
in class weka.classifiers.SingleClassifierEnhancer
options
- the list of options as an array of stringsException
- if an option is not supportedpublic String[] getOptions()
getOptions
in interface weka.core.OptionHandler
getOptions
in class weka.classifiers.SingleClassifierEnhancer
public String toString()
public static void main(String[] argv)
public String getModel()
MultiLabelClassifier
getModel
in interface MultiLabelClassifier
public Map<Integer,Integer> graphType()
MultiLabelDrawable
graphType
in interface MultiLabelDrawable
public Map<Integer,String> graph() throws Exception
MultiLabelDrawable
graph
in interface MultiLabelDrawable
Exception
- if the graph can't be computedpublic void setDebug(boolean debug)
MultiLabelClassifier
setDebug
in interface MultiLabelClassifier
setDebug
in class weka.classifiers.AbstractClassifier
debug
- true if debug output should be printedpublic boolean getDebug()
MultiLabelClassifier
getDebug
in interface MultiLabelClassifier
getDebug
in class weka.classifiers.AbstractClassifier
public String debugTipText()
MultiLabelClassifier
debugTipText
in interface MultiLabelClassifier
debugTipText
in class weka.classifiers.AbstractClassifier
public weka.core.Capabilities getCapabilities()
getCapabilities
in interface weka.classifiers.Classifier
getCapabilities
in interface weka.core.CapabilitiesHandler
getCapabilities
in class weka.classifiers.SingleClassifierEnhancer
public boolean isThreaded()
isThreaded
in interface MultiLabelClassifierThreaded
public void setThreaded(boolean setv)
setThreaded
in interface MultiLabelClassifierThreaded
public double[][] distributionForInstanceM(weka.core.Instances i) throws Exception
distributionForInstanceM
in interface MultiLabelClassifierThreaded
Exception
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