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SUMMARY:Jan Senge
DTSTART:20260302T113000Z
DTEND:20260302T133000Z
DTSTAMP:20260423T005646Z
UID:BNAT/16
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/BNAT/16/">Su
 pport Vector Machines</a>\nby Jan Senge as part of Basic Notions and Appli
 ed 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 se
 minar provides an intuitive introduction to Support Vector Machines (SVMs)
 . We begin with the maximal margin classifier and support vector classifie
 r\, building geometric intuition for how SVMs separate classes with optima
 l margins. We then extend these ideas to the kernel trick\, enabling highl
 y flexible nonlinear decision boundaries through polynomial and radial bas
 is function kernels. The talk also highlights key tuning parameters\, prac
 tical considerations for model fitting\, and strategies for avoiding overf
 itting.\n
LOCATION:https://researchseminars.org/talk/BNAT/16/
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