Re: Spark ML - CrossValidation - How to get Evaluation metrics of best model

Thanks! On Tue, Nov 1, 2016 at 6:30 AM, Sean Owen wrote: > CrossValidator splits the data into k sets, and then trains k times, > holding out one subset for cross-validation each time. You are correct that > you should actually withhold an additional test set, before you use

Re: Spark ML - CrossValidation - How to get Evaluation metrics of best model

CrossValidator splits the data into k sets, and then trains k times, holding out one subset for cross-validation each time. You are correct that you should actually withhold an additional test set, before you use CrossValidator, in order to get an unbiased estimate of the best model's performance.

Spark ML - CrossValidation - How to get Evaluation metrics of best model

I am running classification model. with normal training-test split I can check model accuracy and F1 score using MulticlassClassificationEvaluator. How can I do this with CrossValidation approach? Afaik, you Fit entire sample data in CrossValidator as you don't want to leave out any observation