Package weka.classifiers
Class ParallelIteratedSingleClassifierEnhancer
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.IteratedSingleClassifierEnhancer
weka.classifiers.ParallelIteratedSingleClassifierEnhancer
- All Implemented Interfaces:
Serializable,Cloneable,Classifier,BatchPredictor,CapabilitiesHandler,CapabilitiesIgnorer,CommandlineRunnable,OptionHandler,RevisionHandler
- Direct Known Subclasses:
RandomizableParallelIteratedSingleClassifierEnhancer
public abstract class ParallelIteratedSingleClassifierEnhancer
extends IteratedSingleClassifierEnhancer
Abstract utility class for handling settings common to meta classifiers that
build an ensemble in parallel from a single base learner.
- Version:
- $Revision: 11909 $
- Author:
- Mark Hall (mhall{[at]}pentaho{[dot]}com), Bernhard Pfahringer (bernhard@waikato.ac.nz)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.AbstractClassifier
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidbuildClassifier(Instances data) Stump method for building the classifiersintGet the number of execution slots (threads) to use for building the members of the ensemble.String[]Gets the current settings of the classifier.Returns an enumeration describing the available options.Returns the tip text for this propertyvoidsetNumExecutionSlots(int numSlots) Set the number of execution slots (threads) to use for building the members of the ensemble.voidsetOptions(String[] options) Parses a given list of options.Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer
getNumIterations, numIterationsTipText, setNumIterationsMethods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getCapabilities, getClassifier, postExecution, preExecution, setClassifierMethods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
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Constructor Details
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ParallelIteratedSingleClassifierEnhancer
public ParallelIteratedSingleClassifierEnhancer()
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Method Details
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listOptions
Returns an enumeration describing the available options.- Specified by:
listOptionsin interfaceOptionHandler- Overrides:
listOptionsin classIteratedSingleClassifierEnhancer- Returns:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-num-slots num
Set the number of execution slots to use (default 1 - i.e. no parallelism).Options after -- are passed to the designated classifier.
- Specified by:
setOptionsin interfaceOptionHandler- Overrides:
setOptionsin classIteratedSingleClassifierEnhancer- Parameters:
options- the list of options as an array of strings- Throws:
Exception- if an option is not supported
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getOptions
Gets the current settings of the classifier.- Specified by:
getOptionsin interfaceOptionHandler- Overrides:
getOptionsin classIteratedSingleClassifierEnhancer- Returns:
- an array of strings suitable for passing to setOptions
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setNumExecutionSlots
public void setNumExecutionSlots(int numSlots) Set the number of execution slots (threads) to use for building the members of the ensemble.- Parameters:
numSlots- the number of slots to use.
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getNumExecutionSlots
public int getNumExecutionSlots()Get the number of execution slots (threads) to use for building the members of the ensemble.- Returns:
- the number of slots to use
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numExecutionSlotsTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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buildClassifier
Stump method for building the classifiers- Specified by:
buildClassifierin interfaceClassifier- Overrides:
buildClassifierin classIteratedSingleClassifierEnhancer- Parameters:
data- the training data to be used for generating the ensemble- Throws:
Exception- if the classifier could not be built successfully
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