Improve Random Forest with Linear Models


Random Forest is probably considered by most the silver bullet in supervised prediction tasks. For sure, any data scientist involved in standard machine learning applications is used to fit and benchmark a Random Forest. Random Forest is a well-known algorithm in literature and is proven to reach satisfactory results in both regression and classification contexts. It enjoys the ability to learn complex data relationships with low effort. There are a lot of open-sourced efficient implementations which are available to all of us (the one provided by scikit-learn is for sure the most famous).

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