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Glossary
Machine Learning
Feature Importance

Feature Importance

[ˈfiːtʃər ɪmˈpɔːtəns]
Machine Learning
Last updated: December 9, 2024

Definition

A measure of how much each input feature contributes to a model’s predictions.

Detailed Explanation

Quantitative assessment of the relative importance of input variables in a machine learning model. Can be calculated through various methods including permutation importance, SHAP values, or model-specific measures.

Use Cases

Customer segmentation analysis, risk factor identification, predictive maintenance

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