ModelApplier on multiple Models
I built up a DecisionTree-Model on a Training-Dataset. The Validation is done by a XValidation. After writing down the model I run it over the Test-Dataset with the ModelApplier. This whole Processchain runs perfectly. But: My idea is to find the model which perfectly fits to the Test-Dataset. So I like to build up multiple models by implementing Bagging and evaluate them with the Testdata. The problem is that the ModelApplier can only handle one Model. Do you see an option to run multiple models on a Test-Dataset and evaluate them by ClassificationPerformance?