Last Updated on August 20, 2020 Feature importance refers to techniques that assign a score to input features based on how useful they are at predicting a target variable. There are many types and sources of feature importance scores, although popular examples include statistical correlation scores, coefficients calculated as part of linear models, decision trees, … Continue reading How to Calculate Feature Importance With Python