org.apache.spark.ml.classification

Interface LogisticRegressionTrainingSummary

All Superinterfaces:

LogisticRegressionSummary, java.io.Serializable

All Known Subinterfaces:

BinaryLogisticRegressionTrainingSummary

All Known Implementing Classes:

BinaryLogisticRegressionTrainingSummaryImpl, LogisticRegressionTrainingSummaryImpl

public interface LogisticRegressionTrainingSummary
extends LogisticRegressionSummary

Abstraction for multiclass logistic regression training results. Currently, the training summary ignores the training weights except for the objective trace.

Method Summary

Modifier and Type	Method and Description
double[]	objectiveHistory() objective function (scaled loss + regularization) at each iteration.
int	totalIterations() Number of training iterations.

Methods inherited from interface org.apache.spark.ml.classification.LogisticRegressionSummary

accuracy, asBinary, falsePositiveRateByLabel, featuresCol, fMeasureByLabel, fMeasureByLabel, labelCol, labels, precisionByLabel, predictionCol, predictions, probabilityCol, recallByLabel, truePositiveRateByLabel, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRate

Method Detail

objectiveHistory

double[] objectiveHistory()

objective function (scaled loss + regularization) at each iteration.

totalIterations

int totalIterations()

Number of training iterations.