Interface LogisticRegressionSummary
 All Superinterfaces:
ClassificationSummary
,Serializable
,scala.Serializable
 All Known Subinterfaces:
BinaryLogisticRegressionSummary
,BinaryLogisticRegressionTrainingSummary
,LogisticRegressionTrainingSummary
 All Known Implementing Classes:
BinaryLogisticRegressionSummaryImpl
,BinaryLogisticRegressionTrainingSummaryImpl
,LogisticRegressionSummaryImpl
,LogisticRegressionTrainingSummaryImpl
Abstraction for logistic regression results for a given model.

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

Method Details

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)

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.
