Decision level fusion from parallel classifier

I have three sets of features for predicting the same outputs (normal or abnormal). However, rather than training everything at once by concatenating the features, I'd like to train them independently and then fuse the results (level fusion).

How can I perform it in random forest/kNN/any other classification?

Please assist me by providing a brief example or description.

[MAHMOUD EID]

Have you found an answer?

[VINOTHINI S]

Yes. majority voting based decision we can use

[MAHMOUD EID]

please share an example how to fuse the decisions ?