Package org.apache.spark.ml.tuning
package org.apache.spark.ml.tuning
-
ClassDescriptionK-fold cross validation performs model selection by splitting the dataset into a set of non-overlapping randomly partitioned folds which are used as separate training and test datasets e.g., with k=3 folds, K-fold cross validation will generate 3 (training, test) dataset pairs, each of which uses 2/3 of the data for training and 1/3 for testing.CrossValidatorModel contains the model with the highest average cross-validation metric across folds and uses this model to transform input data.Writer for CrossValidatorModel.Params for
CrossValidatorandCrossValidatorModel.Builder for a param grid used in grid search-based model selection.Validation for hyper-parameter tuning.Model from train validation split.Writer for TrainValidationSplitModel.Params forTrainValidationSplitandTrainValidationSplitModel.Common params forTrainValidationSplitParamsandCrossValidatorParams.