Class LinearSVCTrainingSummaryImpl
Object
org.apache.spark.ml.classification.LinearSVCSummaryImpl
org.apache.spark.ml.classification.LinearSVCTrainingSummaryImpl
- All Implemented Interfaces:
Serializable
,BinaryClassificationSummary
,ClassificationSummary
,LinearSVCSummary
,LinearSVCTrainingSummary
,TrainingSummary
public class LinearSVCTrainingSummaryImpl
extends LinearSVCSummaryImpl
implements LinearSVCTrainingSummary
LinearSVC training results.
param: predictions dataframe output by the model's transform
method.
param: scoreCol field in "predictions" which gives the rawPrediction of each instance.
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: weightCol field in "predictions" which gives the weight of each instance.
param: objectiveHistory objective function (scaled loss + regularization) at each iteration.
- See Also:
-
Constructor Summary
-
Method Summary
Modifier and TypeMethodDescriptiondouble[]
objective function (scaled loss + regularization) at each iteration.Methods inherited from class org.apache.spark.ml.classification.LinearSVCSummaryImpl
areaUnderROC, fMeasureByThreshold, labelCol, pr, precisionByThreshold, predictionCol, predictions, recallByThreshold, roc, scoreCol, weightCol
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.spark.ml.classification.BinaryClassificationSummary
areaUnderROC, fMeasureByThreshold, pr, precisionByThreshold, recallByThreshold, roc, scoreCol
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
Methods inherited from interface org.apache.spark.ml.classification.TrainingSummary
totalIterations
-
Constructor Details
-
LinearSVCTrainingSummaryImpl
-
-
Method Details
-
objectiveHistory
public double[] objectiveHistory()Description copied from interface:TrainingSummary
objective function (scaled loss + regularization) at each iteration. It contains one more element, the initial state, than number of iterations.- Specified by:
objectiveHistory
in interfaceTrainingSummary
- Returns:
- (undocumented)
-