tuning

Type Members

1. class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorParams with Logging

   

   :: Experimental :: K-fold cross validation.

   :: Experimental :: K-fold cross validation.

   Annotations

   @Experimental()

2. class CrossValidatorModel extends Model[CrossValidatorModel] with CrossValidatorParams

   

   :: Experimental :: Model from k-fold cross validation.

   :: Experimental :: Model from k-fold cross validation.

   Annotations

   @Experimental()

3. class ParamGridBuilder extends AnyRef

   

   :: Experimental :: Builder for a param grid used in grid search-based model selection.

   :: Experimental :: Builder for a param grid used in grid search-based model selection.

   Annotations

   @Experimental()

4. class TrainValidationSplit extends Estimator[TrainValidationSplitModel] with TrainValidationSplitParams with Logging

   

   :: Experimental :: Validation for hyper-parameter tuning.

   :: Experimental :: Validation for hyper-parameter tuning. Randomly splits the input dataset into train and validation sets, and uses evaluation metric on the validation set to select the best model. Similar to CrossValidator, but only splits the set once.

   Annotations

   @Experimental()

5. class TrainValidationSplitModel extends Model[TrainValidationSplitModel] with TrainValidationSplitParams

   

   :: Experimental :: Model from train validation split.

   :: Experimental :: Model from train validation split.

   Annotations

   @Experimental()