Multiclass Support Vector Machine

Organizer
Marina Leal Palazón
Lugar
Seminario I (IMUS), Edificio Celestino Mutis
Autor
Alberto Japón Saez
Tipo de evento
Descripción

Support Vector Machine is one of the most popular techniques in machine learning. Due to its success in binary classification, many options have been proposed to extend this technique for multi class classification problems. In this talk we present a novel approach to construct multiclass clasiffiers by means of arrangements of hyperplanes. We propose different mixed integer non linear programming formulations for the problem by using extensions of widely  used measures for misclassifying observations.