Package weka.classifiers.evaluation
Interface StandardEvaluationMetric
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public interface StandardEvaluationMetricPrimarily a marker interface for a "standard" evaluation metric - i.e. one that would be part of the normal output in Weka without having to turn specific display options.- Version:
- $Revision: 9320 $
- Author:
- Mark Hall (mhall{[at]}pentaho{[dot]}com)
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description java.lang.StringtoSummaryString()Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.voidupdateStatsForClassifier(double[] predictedDistribution, Instance instance)Updates the statistics about a classifiers performance for the current test instance.voidupdateStatsForPredictor(double predictedValue, Instance instance)Updates the statistics about a predictors performance for the current test instance.
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Method Detail
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toSummaryString
java.lang.String toSummaryString()
Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.- Returns:
- a formatted string containing all the computed statistics
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updateStatsForClassifier
void updateStatsForClassifier(double[] predictedDistribution, Instance instance) throws java.lang.ExceptionUpdates the statistics about a classifiers performance for the current test instance. Gets called when the class is nominal. Implementers need only implement this method if it is not possible to compute their statistics from what is stored in the base Evaluation object.- Parameters:
predictedDistribution- the probabilities assigned to each classinstance- the instance to be classified- Throws:
java.lang.Exception- if the class of the instance is not set
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updateStatsForPredictor
void updateStatsForPredictor(double predictedValue, Instance instance) throws java.lang.ExceptionUpdates the statistics about a predictors performance for the current test instance. Gets called when the class is numeric. Implementers need only implement this method if it is not possible to compute their statistics from what is stored in the base Evaluation object.- Parameters:
predictedValue- the numeric value the classifier predictsinstance- the instance to be classified- Throws:
java.lang.Exception- if the class of the instance is not set
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