Recursive Feature Ellimination is a feature selection method which uses a given model's measure of feature importance to sequentially remove features. The following steps are repeated until the desired number of features is reached: (1) fit the model to the current set of features; (2) rank the features by importance; (3) remove one or more of the least important features.