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 TypeMethodDescriptiondouble[]
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.
-