Package org.apache.spark.ml.classification

Class RandomForestClassificationTrainingSummaryImpl

Object

org.apache.spark.ml.classification.RandomForestClassificationSummaryImpl

org.apache.spark.ml.classification.RandomForestClassificationTrainingSummaryImpl

All Implemented Interfaces:

Serializable, ClassificationSummary, RandomForestClassificationSummary, RandomForestClassificationTrainingSummary, TrainingSummary, scala.Serializable

public class RandomForestClassificationTrainingSummaryImpl
extends RandomForestClassificationSummaryImpl
implements RandomForestClassificationTrainingSummary

Multiclass RandomForestClassification training results.

param: predictions dataframe output by the model's transform method. 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
RandomForestClassificationTrainingSummaryImpl(Dataset<Row> predictions, 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.RandomForestClassificationSummaryImpl

labelCol, predictionCol, predictions, 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.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.RandomForestClassificationSummary

asBinary

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

totalIterations

Constructor Details

RandomForestClassificationTrainingSummaryImpl

public RandomForestClassificationTrainingSummaryImpl(Dataset<Row> predictions,
 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)