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.
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Method SummaryModifier and TypeMethodDescriptiondouble[]objective function (scaled loss + regularization) at each iteration.intNumber of training iterations.
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Method Details- 
objectiveHistorydouble[] objectiveHistory()objective function (scaled loss + regularization) at each iteration. It contains one more element, the initial state, than number of iterations.- Returns:
- (undocumented)
 
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totalIterationsint totalIterations()Number of training iterations.
 
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