Linear Model Selection and Regularization (Part 1)
Mateusz Masłowski (Dioscuri Centre in Topological Data Analysis)
| Mon Jan 12, 11:30-13:30 (3 days from now) | |
| Lecture held in Room 1 at the IMPAS, Room 1.14 at the Institute of Informatics (University of Gdańsk). |
Abstract: This session, based on the first half of Chapter 6 of An Introduction to Statistical Learning with Applications in Python, explores Linear Model Selection techniques for improving model interpretability and performance. We’ll cover best subset, forward, and backward stepwise selection, discussing how these approaches identify the most informative predictors and balance complexity with predictive power.
Computer scienceMathematics
Audience: general audience
Basic Notions and Applied Topology Seminar
| Organizer: | Julian Brüggemann |
| Curator: | John Rick* |
| *contact for this listing |
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