org.apache.spark.ml.classification

Class BinaryLogisticRegressionTrainingSummary

Object

org.apache.spark.ml.classification.BinaryLogisticRegressionSummary

org.apache.spark.ml.classification.BinaryLogisticRegressionTrainingSummary

All Implemented Interfaces:

java.io.Serializable, LogisticRegressionSummary, LogisticRegressionTrainingSummary

public class BinaryLogisticRegressionTrainingSummary
extends BinaryLogisticRegressionSummary
implements LogisticRegressionTrainingSummary

:: Experimental :: Logistic regression training results.

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: 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.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
double[]	objectiveHistory() objective function (scaled loss + regularization) at each iteration.

Methods inherited from class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary

areaUnderROC, featuresCol, fMeasureByThreshold, labelCol, pr, precisionByThreshold, predictions, probabilityCol, recallByThreshold, roc

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

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

totalIterations

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

featuresCol, labelCol, predictions, probabilityCol

Method Detail

objectiveHistory

public double[] objectiveHistory()

Description copied from interface: LogisticRegressionTrainingSummary

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

Specified by:

objectiveHistory in interface LogisticRegressionTrainingSummary