Optimal arrangements of hyperplanes for SVM-based multiclass classification

Description

In this paper, we present a novel approach to construct multiclass classifiers by means of arrangements of hyperplanes. We propose different mixed integer (linear and non linear) programming formulations for the problem using extensions of widely used measures for misclassifying observations where the kernel trick can be adapted to be applicable. Some dimensionality reductions and variable fixing strategies are also developed for these models. An extensive battery of experiments has been run which reveal the powerfulness of our proposal as compared with other previously proposed methodologies.

Abstract

Ministerio de Economía y Competitividad (MINECO). España

Abstract

Universidad de Granada

Abstract

Junta de Andalucía

Additional details