What is Feature Importance In Machine Learning?
Feature Importance
Feature importance is a compilation of a class of explainability techniques that take in all the features related to making a model prediction and assign a certain score to each feature to weigh how much or how little it impacted the outcome. These scores can then be used to better understand the internal logic of a model, make necessary changes to the model to improve its accuracy, and also reduce unnecessary inputs.