Class LinearSVCTrainingSummaryImpl
Object
org.apache.spark.ml.classification.LinearSVCSummaryImpl
org.apache.spark.ml.classification.LinearSVCTrainingSummaryImpl
- All Implemented Interfaces:
- Serializable,- BinaryClassificationSummary,- ClassificationSummary,- LinearSVCSummary,- LinearSVCTrainingSummary,- TrainingSummary,- Summary
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:
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Constructor SummaryConstructors
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Method SummaryModifier and TypeMethodDescriptiondouble[]objective function (scaled loss + regularization) at each iteration.Methods inherited from class org.apache.spark.ml.classification.LinearSVCSummaryImplareaUnderROC, fMeasureByThreshold, labelCol, pr, precisionByThreshold, predictionCol, predictions, recallByThreshold, roc, scoreCol, weightColMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.apache.spark.ml.classification.BinaryClassificationSummaryareaUnderROC, fMeasureByThreshold, pr, precisionByThreshold, recallByThreshold, roc, scoreColMethods inherited from interface org.apache.spark.ml.classification.ClassificationSummaryaccuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labelCol, labels, precisionByLabel, predictionCol, predictions, recallByLabel, truePositiveRateByLabel, weightCol, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRateMethods inherited from interface org.apache.spark.ml.classification.TrainingSummarytotalIterations
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Constructor Details- 
LinearSVCTrainingSummaryImpl
 
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Method Details- 
objectiveHistorypublic double[] objectiveHistory()Description copied from interface:TrainingSummaryobjective function (scaled loss + regularization) at each iteration. It contains one more element, the initial state, than number of iterations.- Specified by:
- objectiveHistoryin interface- TrainingSummary
- Returns:
- (undocumented)
 
 
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