Is it possible to build a RandomForest over KNN, linear models, and neural networks? Why?

RandomForest is an ensemble method that builds multiple decision trees on random subsets of data and features. It is designed for decision trees, which are the base models in this algorithm.

You cannot build a "RandomForest" on top of KNN, linear models, or neural networks in the traditional sense, because RandomForest is not an ensemble of arbitrary models but a specific algorithm using decision trees.

If talking about ensembles generally, you can create ensembles of different models (e.g., stacking), where base models include KNN, linear models, neural networks, etc. But that is not called RandomForest.

Summary:

• RandomForest is built from decision trees.
• KNN, linear models, or neural networks cannot be used as base models inside a RandomForest.
• To combine different models, other ensemble methods like bagging, boosting, stacking are used.