Package org.apache.spark.ml.classification

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:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
LinearSVCTrainingSummaryImpl(Dataset<Row> predictions, String scoreCol, String predictionCol, String labelCol, String weightCol, double[] objectiveHistory)

Method Summary

Modifier and Type	Method	Description
double[]	objectiveHistory()	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

public LinearSVCTrainingSummaryImpl(Dataset<Row> predictions,
 String scoreCol,
 String predictionCol,
 String labelCol,
 String weightCol,
 double[] objectiveHistory)

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 interface TrainingSummary

Returns:

(undocumented)