public class BinaryRandomForestClassificationTrainingSummaryImpl extends BinaryRandomForestClassificationSummaryImpl implements BinaryRandomForestClassificationTrainingSummary
param: predictions dataframe output by the model's transform
method.
param: scoreCol field in "predictions" which gives the probability of each class as a vector.
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.
Constructor and Description |
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BinaryRandomForestClassificationTrainingSummaryImpl(Dataset<Row> predictions,
String scoreCol,
String predictionCol,
String labelCol,
String weightCol,
double[] objectiveHistory) |
Modifier and Type | Method and Description |
---|---|
double[] |
objectiveHistory()
objective function (scaled loss + regularization) at each iteration.
|
areaUnderROC, fMeasureByThreshold, pr, precisionByThreshold, recallByThreshold, roc, scoreCol
labelCol, predictionCol, predictions, weightCol
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
areaUnderROC, fMeasureByThreshold, pr, precisionByThreshold, recallByThreshold, roc, scoreCol
asBinary
accuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labelCol, labels, precisionByLabel, predictionCol, predictions, recallByLabel, truePositiveRateByLabel, weightCol, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRate
totalIterations
public double[] objectiveHistory()
TrainingSummary
objectiveHistory
in interface TrainingSummary