Tuning machine learning models in Spark involves selecting the best performing parameters for a model using CrossValidator or TrainValidationSplit. This process uses a parameter grid where a model is trained for each combination of parameters and evaluated according to a metric. Prior to Spark 2.3, running CrossValidator or TrainValidationSplit will train and evaluate one model at a time in serial, until each combination in the parameter grid has been evaluated. Spark of course will perform d...
