public class BinaryLogisticRegressionTrainingSummaryImpl extends BinaryLogisticRegressionSummaryImpl implements BinaryLogisticRegressionTrainingSummary
param: predictions dataframe output by the model's
param: probabilityCol field in "predictions" which gives the probability of
each class as a vector.
param: predictionCol field in "predictions" which gives the prediction for a data instance as a
param: labelCol field in "predictions" which gives the true label of each instance.
param: featuresCol field in "predictions" which gives the features of each instance as a vector.
param: objectiveHistory objective function (scaled loss + regularization) at each iteration.
|Constructor and Description|
|Modifier and Type||Method and Description|
objective function (scaled loss + regularization) at each iteration.
featuresCol, labelCol, predictionCol, predictions, probabilityCol
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
areaUnderROC, binaryMetrics, fMeasureByThreshold, pr, precisionByThreshold, recallByThreshold, roc, sparkSession
accuracy, asBinary, falsePositiveRateByLabel, featuresCol, fMeasureByLabel, fMeasureByLabel, labelCol, labels, multiclassMetrics, precisionByLabel, predictionCol, predictions, probabilityCol, recallByLabel, truePositiveRateByLabel, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRate