@KFStep(name="ClassifierPerformanceEvaluator", category="Evaluation", toolTipText="Evaluates batch classifiers", iconPath="weka/gui/knowledgeflow/icons/ClassifierPerformanceEvaluator.gif") public class ClassifierPerformanceEvaluator extends BaseStep
Constructor and Description |
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ClassifierPerformanceEvaluator()
Constructor
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Modifier and Type | Method and Description |
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boolean |
getCollectPredictionsForVisAndAUC() |
java.lang.String |
getCostMatrixString()
Get the cost matrix to use as a string
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java.lang.String |
getCustomEditorForStep()
Return the fully qualified name of a custom editor component (JComponent)
to use for editing the properties of the step.
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boolean |
getErrorPlotPointSizeProportionalToMargin()
Get whether the size of plot data points will be proportional to the
prediction margin
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boolean |
getEvaluateWithRespectToCosts()
Get whether to evaluate with respoect to costs
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java.lang.String |
getEvaluationMetricsToOutput()
Get the evaluation metrics to output (as a comma-separated list).
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java.util.List<java.lang.String> |
getIncomingConnectionTypes()
Get a list of incoming connection types that this step can accept.
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java.util.List<java.lang.String> |
getOutgoingConnectionTypes()
Get a list of outgoing connection types that this step can produce.
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boolean |
getOutputConfusionMatrix() |
boolean |
getOutputEntropyMetrics() |
boolean |
getOutputPerClassStats() |
void |
processIncoming(Data data)
Process an incoming data payload (if the step accepts incoming connections)
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void |
setCollectPredictionsForVisAndAUC(boolean collectPredictionsForVisAndAUC) |
void |
setCostMatrixString(java.lang.String cms)
Set the cost matrix to use as a string
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void |
setErrorPlotPointSizeProportionalToMargin(boolean e)
Set whether the size of plot data points will be proportional to the
prediction margin
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void |
setEvaluateWithRespectToCosts(boolean useCosts)
Set whether to evaluate with respoect to costs
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void |
setEvaluationMetricsToOutput(java.lang.String m)
Set the evaluation metrics to output (as a comma-separated list).
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void |
setOutputConfusionMatrix(boolean outputConfusionMatrix) |
void |
setOutputEntropyMetrics(boolean outputEntropyMetrics) |
void |
setOutputPerClassStats(boolean perClassStats) |
void |
stepInit()
Initialize the step.
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void |
stop()
Request that processing be stopped.
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environmentSubstitute, getDefaultSettings, getInteractiveViewers, getInteractiveViewersImpls, getName, getStepManager, globalInfo, isResourceIntensive, isStopRequested, outputStructureForConnectionType, outputStructureForConnectionType, setName, setStepIsResourceIntensive, setStepManager, setStepMustRunSingleThreaded, start, stepMustRunSingleThreaded
public ClassifierPerformanceEvaluator()
public void setOutputPerClassStats(boolean perClassStats)
@OptionMetadata(displayName="Output per-class stats", description="Output precision/recall and true/false positives for each class", displayOrder=1) public boolean getOutputPerClassStats()
@OptionMetadata(displayName="Output confusion matrix", description="Output the matrix containing class confusions", displayOrder=2) public void setOutputConfusionMatrix(boolean outputConfusionMatrix)
public boolean getOutputConfusionMatrix()
@OptionMetadata(displayName="Output entropy evaluation measures", description="Output entropy-based evaluation measures", displayOrder=3) public void setOutputEntropyMetrics(boolean outputEntropyMetrics)
public boolean getOutputEntropyMetrics()
@OptionMetadata(displayName="Collect test data and predictions for visualization", description="Collect data and predictions in order to output visualizableError and thresholdData data", displayOrder=4) public void setCollectPredictionsForVisAndAUC(boolean collectPredictionsForVisAndAUC)
public boolean getCollectPredictionsForVisAndAUC()
@OptionMetadata(displayName="Error plot point size proportional to margin", description="Set the point size proportional to the prediction margin for classification error plots") public boolean getErrorPlotPointSizeProportionalToMargin()
public void setErrorPlotPointSizeProportionalToMargin(boolean e)
e
- true if plot data points will be rendered proportional to the size
of the prediction margin@ProgrammaticProperty public java.lang.String getEvaluationMetricsToOutput()
public void setEvaluationMetricsToOutput(java.lang.String m)
m
- the evaluation metrics to output@ProgrammaticProperty public void setEvaluateWithRespectToCosts(boolean useCosts)
useCosts
- true to use cost-sensitive evaluationpublic boolean getEvaluateWithRespectToCosts()
@ProgrammaticProperty public void setCostMatrixString(java.lang.String cms)
cms
- the cost matrix to usepublic java.lang.String getCostMatrixString()
public java.util.List<java.lang.String> getIncomingConnectionTypes()
public java.util.List<java.lang.String> getOutgoingConnectionTypes()
public void stepInit() throws WekaException
Step
WekaException
- if a problem occurs during initializationpublic void stop()
BaseStep
isStopRequested()
periodically to see if they should stop
processing.public void processIncoming(Data data) throws WekaException
processIncoming
in interface BaseStepExtender
processIncoming
in interface Step
processIncoming
in class BaseStep
data
- the payload to processWekaException
- if a problem occurspublic java.lang.String getCustomEditorForStep()
getCustomEditorForStep
in interface Step
getCustomEditorForStep
in class BaseStep