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SUMMARY:Mateusz Masłowski (Dioscuri Centre in Topological Data Analysis)
DTSTART:20260112T113000Z
DTEND:20260112T133000Z
DTSTAMP:20260423T024552Z
UID:BNAT/10
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/BNAT/10/">Li
 near Model Selection and Regularization (Part 1)</a>\nby Mateusz Masłowsk
 i (Dioscuri Centre in Topological Data Analysis) as part of Basic Notions 
 and Applied Topology Seminar\n\nLecture held in Room 1 at the IMPAS\, Room
  1.14 at the Institute of Informatics (University of Gdańsk).\n\nAbstract
 \nThis session\, based on the first half of Chapter 6 of An Introduction t
 o 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 a
 nd balance complexity with predictive power.\n
LOCATION:https://researchseminars.org/talk/BNAT/10/
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