Best Practice to Calculate and Interpret Model Feature Importance

With an example of Random Forest model

All images unless otherwise noted are by the author.

In machine learning, most of the time you want a model that is not only accurate but also interpretable. One example is customer churn prediction — in addition to knowing who will churn, it’s equally important to understand which variables are critical in predicting churn to help improve our service and product.

Popular machine learning packages such as …

data science feature feature-importance hands-on-tutorials importance machine learning random-forest