Interface LogisticRegressionSummary
- All Superinterfaces:
ClassificationSummary
,Serializable
- All Known Subinterfaces:
BinaryLogisticRegressionSummary
,BinaryLogisticRegressionTrainingSummary
,LogisticRegressionTrainingSummary
- All Known Implementing Classes:
BinaryLogisticRegressionSummaryImpl
,BinaryLogisticRegressionTrainingSummaryImpl
,LogisticRegressionSummaryImpl
,LogisticRegressionTrainingSummaryImpl
Abstraction for logistic regression results for a given model.
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Method Summary
Modifier and TypeMethodDescriptionasBinary()
Convenient method for casting to binary logistic regression summary.Field in "predictions" which gives the features of each instance as a vector.Field in "predictions" which gives the probability of each class as a vector.Methods inherited from interface org.apache.spark.ml.classification.ClassificationSummary
accuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labelCol, labels, precisionByLabel, predictionCol, predictions, recallByLabel, truePositiveRateByLabel, weightCol, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRate
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Method Details
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asBinary
BinaryLogisticRegressionSummary asBinary()Convenient method for casting to binary logistic regression summary. This method will throw an Exception if the summary is not a binary summary.- Returns:
- (undocumented)
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featuresCol
String featuresCol()Field in "predictions" which gives the features of each instance as a vector. -
probabilityCol
String probabilityCol()Field in "predictions" which gives the probability of each class as a vector.
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