This repository contains project materials for the Spring 2024 STAT 208 class, specifically for Team 8. All materials are the property of Team 8, University of California, Riverside, A. Gary Anderson School of Management. Thank you for viewing our repository.
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Section III Part 4: Feature Importance Analysis #17
Identify which features are most important in predicting the target values.
For feature importance analysis, one can use Random Forest, Gradient Boosting, or Regression Analysis.
Jen-uis
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3 months ago
Identify which features are most important in predicting the target values. For feature importance analysis, one can use Random Forest, Gradient Boosting, or Regression Analysis.