An educational talk about Feature Selection and Feature Engineering and why it matters.
- an introduction to why feature selection is an essential step in building DS and ML pipelines.
- an introduction to basic feature engineering.
- an exhaustive guide to feature engineering.
- a one-fits-all solution guide.
establish an intuition about where to focus efforts when creating DS and ML pipelines.
(assuming a dataset post preparation and cleaning steps is available)
Note: the content of this education talk is also being used in presentations.
slide deck used in the presentations and video materials
used in the presentations and video materials.
Note: these notebooks have been developed using older versions of packages (particularly scikit-learn). They have not been verified with current versions.
Demo Notebook Feature Selection
Demo Notebook Feature Engineering
Madelon Dataset paper
Design of experiments for the NIPS 2003 variable selection benchmark
Isabelle Guyon – July 2003
Copy of the Dataset
Boruta Feature Selection Heuristic
Feature Selection with the Boruta Package
Miron B. Kursa (University of Warsaw)
Witold R. Rudnicki (University of Warsaw)
- Overview
- Feature Selection
- Feature Selection notebook
- Feature Engineering
- Feature Engineering notebook
- Remarks and Results
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Terms as outlined on main page are applicable.
These materials are governed by the BSD-3 license. Details