public class BinaryLogisticRegressionTrainingSummaryImpl extends BinaryLogisticRegressionSummaryImpl implements BinaryLogisticRegressionTrainingSummary
param: predictions dataframe output by the model's transform method.
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
double.
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 |
|---|
BinaryLogisticRegressionTrainingSummaryImpl(Dataset<Row> predictions,
String probabilityCol,
String predictionCol,
String labelCol,
String featuresCol,
double[] objectiveHistory) |
| Modifier and Type | Method and Description |
|---|---|
double[] |
objectiveHistory()
objective function (scaled loss + regularization) at each iteration.
|
featuresCol, labelCol, predictionCol, predictions, probabilityColequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitareaUnderROC, binaryMetrics, fMeasureByThreshold, pr, precisionByThreshold, recallByThreshold, roc, sparkSessiontotalIterationsaccuracy, asBinary, falsePositiveRateByLabel, featuresCol, fMeasureByLabel, fMeasureByLabel, labelCol, labels, multiclassMetrics, precisionByLabel, predictionCol, predictions, probabilityCol, recallByLabel, truePositiveRateByLabel, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRatepublic double[] objectiveHistory()
LogisticRegressionTrainingSummaryobjectiveHistory in interface LogisticRegressionTrainingSummary