Package weka.knowledgeflow.steps
Class ASEvaluator
java.lang.Object
weka.knowledgeflow.steps.BaseStep
weka.knowledgeflow.steps.WekaAlgorithmWrapper
weka.knowledgeflow.steps.ASEvaluator
- All Implemented Interfaces:
Serializable,BaseStepExtender,Step
@KFStep(name="ASEvaluator",
category="AttSelection",
toolTipText="Weka attribute selection evaluator wrapper",
iconPath="",
resourceIntensive=true)
public class ASEvaluator
extends WekaAlgorithmWrapper
Step that wraps a Weka attribute or subset evaluator. Handles training and
test set connections. Requires an ASSearchStrategy step to be connected via
an "info" connection. Will output both attribute selection results (via text
connections) and transformed data (via outgoing train or test set
connections). When processing multiple incoming training and test folds, the
step can either output a cross-validation style summary over all the folds or
individual attribute selection results for each fold.
- Version:
- $Revision: $
- Author:
- Mark Hall (mhall{[at]}pentaho{[dot]}com)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionGet the class name of the custom editor for this stepGet the evaluator wrapped by this stepGet incoming connections accepted given the current state of the stepGet a list of output connections that can be produced given the current state of the stepbooleanGet whether to output separate results for each fold of a cross-validation, rather than averaging over folds.Get the class of Weka algorithm wrapped by this wrappervoidprocessIncoming(Data data) Process an incoming Data objectvoidsetEvaluator(ASEvaluation eval) Set the evaluator to wrap (just calls setWrappedAlgorithm)voidsetTreatXValFoldsSeparately(boolean treatSeparately) Set whether to output separate results for each fold of a cross-validation, rather than averaging over folds.voidsetWrappedAlgorithm(Object algo) Set an instance of the wrapped algorithm to usevoidstepInit()Initialize at the start of a runMethods inherited from class weka.knowledgeflow.steps.WekaAlgorithmWrapper
getDefaultIconPath, getDefaultPackageLevelIconPath, getIconPath, getWrappedAlgorithm, globalInfoMethods inherited from class weka.knowledgeflow.steps.BaseStep
environmentSubstitute, getDefaultSettings, getInteractiveViewers, getInteractiveViewersImpls, getName, getStepManager, isResourceIntensive, isStopRequested, outputStructureForConnectionType, outputStructureForConnectionType, setName, setStepIsResourceIntensive, setStepManager, setStepMustRunSingleThreaded, start, stepMustRunSingleThreaded, stop
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Constructor Details
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ASEvaluator
public ASEvaluator()
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Method Details
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getWrappedAlgorithmClass
Get the class of Weka algorithm wrapped by this wrapper- Specified by:
getWrappedAlgorithmClassin classWekaAlgorithmWrapper- Returns:
- the wrapped algorithm class
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setWrappedAlgorithm
Set an instance of the wrapped algorithm to use- Overrides:
setWrappedAlgorithmin classWekaAlgorithmWrapper- Parameters:
algo- the algorithm to use
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getEvaluator
Get the evaluator wrapped by this step- Returns:
- the attribute or subset evaluator wrapped by this step
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setEvaluator
Set the evaluator to wrap (just calls setWrappedAlgorithm)- Parameters:
eval- the evaluator to use
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setTreatXValFoldsSeparately
@OptionMetadata(displayName="Treat x-val folds separately", description="Output separate attribute selection results for each fold of a cross-validation (rather than averaging across folds)") public void setTreatXValFoldsSeparately(boolean treatSeparately) Set whether to output separate results for each fold of a cross-validation, rather than averaging over folds.- Parameters:
treatSeparately- true if each fold will have results output
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getTreatXValFoldsSeparately
public boolean getTreatXValFoldsSeparately()Get whether to output separate results for each fold of a cross-validation, rather than averaging over folds.- Returns:
- true if each fold will have results output
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stepInit
Initialize at the start of a run- Throws:
WekaException- if there is an illegal configuration (i.e. Ranker search with subset evaluator or regular search with attribute evaluator
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processIncoming
Process an incoming Data object- Specified by:
processIncomingin interfaceBaseStepExtender- Specified by:
processIncomingin interfaceStep- Overrides:
processIncomingin classBaseStep- Parameters:
data- the data object to process- Throws:
WekaException- if a problem occurs
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getIncomingConnectionTypes
Get incoming connections accepted given the current state of the step- Returns:
- a list of acceptable incoming connections
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getOutgoingConnectionTypes
Get a list of output connections that can be produced given the current state of the step- Returns:
- a list of output connections
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getCustomEditorForStep
Get the class name of the custom editor for this step- Specified by:
getCustomEditorForStepin interfaceStep- Overrides:
getCustomEditorForStepin classBaseStep- Returns:
- the class name of the custom editor for this step
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