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Feature selection notebooks

DataRobot offers end-to-end code examples via Jupyter notebooks that help you find complete examples of common data science and machine learning workflows. Review the notebooks that outline feature selection below.

Topic Describes... Download link
Feature Importance Rank Ensembling Learn about the benefits of Feature Importance Rank Ensembling (FIRE)—a method of advanced feature selection that uses a median rank aggregation of feature impacts across several models created during a run of Autopilot. Download
Advanced feature selection with R Use R to select features by creating aggregated feature impact. N/A

Updated March 28, 2022
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