What is feature importance in machine learning?

What is feature importance in machine learning?

Feature importance refers to techniques that assign a score to input features based on how useful they are at predicting the target variable.

How can I calculate feature importance in Python?

You can use libraries like scikit-learn, which provides methods like feature_importances_ for tree-based models.

Can you give me an example using a decision tree?

Sure! After training a decision tree model, you can access model.feature_importances_ to see the importance scores for each feature.

What are some common methods to evaluate feature importance?

Common methods include permutation importance, SHAP values, and LIME, each providing different insights into feature contributions.