Question

Now you have a feasible amount of predictors, but you’re fairly sure that you don’t need all of them. How would you perform feature selection on the dataset?

Answer 1

Feature selection can be performed by using a variety of methods, such as forward selection, backward elimination, or recursive feature elimination. Forward selection involves starting with an empty set of features and adding features one at a time until the model performance is maximized. Backward elimination involves starting with all features and removing features one at a time until the model performance is maximized. Recursive feature elimination involves recursively removing features and building a model on the remaining features until the model performance is maximized.