public class RandomCommittee extends RandomizableParallelIteratedSingleClassifierEnhancer implements WeightedInstancesHandler, PartitionGenerator
-S <num> Random number seed. (default 1)
-I <num> Number of iterations. (default 10)
-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.RandomTree)
Options specific to classifier weka.classifiers.trees.RandomTree:
-K <number of attributes> Number of attributes to randomly investigate (<1 = int(log(#attributes)+1)).
-M <minimum number of instances> Set minimum number of instances per leaf.
-S <num> Seed for random number generator. (default 1)
-depth <num> The maximum depth of the tree, 0 for unlimited. (default 0)
-D If set, classifier is run in debug mode and may output additional info to the consoleOptions after -- are passed to the designated classifier.
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT
Constructor and Description |
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RandomCommittee()
Constructor.
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Modifier and Type | Method and Description |
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void |
buildClassifier(Instances data)
Builds the committee of randomizable classifiers.
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double[] |
distributionForInstance(Instance instance)
Calculates the class membership probabilities for the given test
instance.
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void |
generatePartition(Instances data)
Builds the classifier to generate a partition.
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double[] |
getMembershipValues(Instance inst)
Computes an array that indicates leaf membership
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java.lang.String |
getRevision()
Returns the revision string.
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java.lang.String |
globalInfo()
Returns a string describing classifier
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static void |
main(java.lang.String[] argv)
Main method for testing this class.
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int |
numElements()
Returns the number of elements in the partition.
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java.lang.String |
toString()
Returns description of the committee.
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getOptions, getSeed, listOptions, seedTipText, setOptions, setSeed
getNumExecutionSlots, numExecutionSlotsTipText, setNumExecutionSlots
getNumIterations, numIterationsTipText, setNumIterations
classifierTipText, getCapabilities, getClassifier, postExecution, preExecution, setClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
getCapabilities
public java.lang.String globalInfo()
public void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in interface Classifier
buildClassifier
in class ParallelIteratedSingleClassifierEnhancer
data
- the training data to be used for generating the
bagged classifier.java.lang.Exception
- if the classifier could not be built successfullypublic double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in interface Classifier
distributionForInstance
in class AbstractClassifier
instance
- the instance to be classifiedjava.lang.Exception
- if distribution can't be computed successfullypublic java.lang.String toString()
toString
in class java.lang.Object
public void generatePartition(Instances data) throws java.lang.Exception
generatePartition
in interface PartitionGenerator
java.lang.Exception
public double[] getMembershipValues(Instance inst) throws java.lang.Exception
getMembershipValues
in interface PartitionGenerator
java.lang.Exception
public int numElements() throws java.lang.Exception
numElements
in interface PartitionGenerator
java.lang.Exception
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class AbstractClassifier
public static void main(java.lang.String[] argv)
argv
- the options