Open israel-cj opened 9 months ago
Hi there,
You could try fit_base_estimators=False
, i.e.,
stacked_ensemble = StackingClassifier(
classifiers=base_models,
meta_classifier=meta_model,
use_probas=True,
average_probas=False,
fit_base_estimators=False
)
Dear,
I hope you are doing great! Thank you for the work done in mlxtend. I have the next problem: Let’s say I have a list of pipelines called ‘get_pipelines’, where each pipeline contains preprocessing steps such as ColumnTransformer, SimpleImputer, etc. Each pipeline independently works when I want to fit/predict on my dataset. Nevertheless, if I do the stacking the preprocessing steps are not being considered since I get errors saying my data should be transformed from categorical to numerical, etc. when that is already done for each pipeline. Is there a way to ask the Stacking to use such preprocessing? My code looks like this (THANK YOU):