Multiclass optimal classification trees with SVM-splits

Author:

Blanco Víctor,Japón AlbertoORCID,Puerto Justo

Abstract

AbstractIn this paper we present a novel mathematical optimization-based methodology to construct tree-shaped classification rules for multiclass instances. Our approach consists of building Classification Trees in which, except for the leaf nodes, the labels are temporarily left out and grouped into two classes by means of a SVM separating hyperplane. We provide a Mixed Integer Non Linear Programming formulation for the problem and report the results of an extended battery of computational experiments to assess the performance of our proposal with respect to other benchmarking classification methods.

Funder

Agencia Estatal de Investigación

Junta de Andalucía

Universidad de Sevilla

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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