Interface TrainingSummary

All Known Subinterfaces:
BinaryLogisticRegressionTrainingSummary, BinaryRandomForestClassificationTrainingSummary, FMClassificationTrainingSummary, LinearSVCTrainingSummary, LogisticRegressionTrainingSummary, MultilayerPerceptronClassificationTrainingSummary, RandomForestClassificationTrainingSummary
All Known Implementing Classes:
BinaryLogisticRegressionTrainingSummaryImpl, BinaryRandomForestClassificationTrainingSummaryImpl, FMClassificationTrainingSummaryImpl, LinearSVCTrainingSummaryImpl, LogisticRegressionTrainingSummaryImpl, MultilayerPerceptronClassificationTrainingSummaryImpl, RandomForestClassificationTrainingSummaryImpl

public interface TrainingSummary
Abstraction for training results.
  • Method Summary

    Modifier and Type
    Method
    Description
    double[]
    objective function (scaled loss + regularization) at each iteration.
    int
    Number of training iterations.
  • Method Details

    • objectiveHistory

      double[] objectiveHistory()
      objective function (scaled loss + regularization) at each iteration. It contains one more element, the initial state, than number of iterations.
      Returns:
      (undocumented)
    • totalIterations

      int totalIterations()
      Number of training iterations.