Thanks @ptrblck

Yes, I want to extract the weights  of the embeddings layers (wich essentialy have captured semantic relationships between the labels o levels of a catagorical feature during the training of my NN) and treat them as feature for a Random Forest model … Obviously, I would use the same originals datasets. The change comes in the  form of using the embeddings instead of some other encoder technique (like LabelEncoder or OneHot, wich don’t provide meanindull relationships between the categorical features and its levels). I’ll also use, of course the numerical continius features.

In a nutshell, my new dataset for a Random Forest model would be embeddings + continius features (embeddings replacing categorical features)
I hope I’ve explained myself well
Best regards