Class BinaryLogisticRegressionTrainingSummaryImpl

All Implemented Interfaces:
Serializable, BinaryClassificationSummary, BinaryLogisticRegressionSummary, BinaryLogisticRegressionTrainingSummary, ClassificationSummary, LogisticRegressionSummary, LogisticRegressionTrainingSummary, TrainingSummary

public class BinaryLogisticRegressionTrainingSummaryImpl extends BinaryLogisticRegressionSummaryImpl implements BinaryLogisticRegressionTrainingSummary
Binary logistic regression training results.

param: predictions dataframe output by the model's transform method. param: probabilityCol 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: featuresCol field in "predictions" which gives the features of each instance as a vector. 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 Details

    • BinaryLogisticRegressionTrainingSummaryImpl

      public BinaryLogisticRegressionTrainingSummaryImpl(Dataset<Row> predictions, String probabilityCol, String predictionCol, String labelCol, String featuresCol, 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)