ICF: An algorithm for large scale classification with conic functions

ÇİMEN E., ÖZTÜRK G., GEREK Ö. N.

SOFTWAREX, vol.8, pp.59-63, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 8
  • Publication Date: 2018
  • Doi Number: 10.1016/j.softx.2017.12.003
  • Journal Name: SOFTWAREX
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.59-63
  • Keywords: Polyhedral conic functions, Mathematical programming, Classification, Machine learning, SEPARATION
  • Anadolu University Affiliated: Yes

Abstract

Incremental Conic Functions (ICF) algorithm is developed for solving classification problems based on mathematical programming. This algorithm improves previous version of conic function-based classifier construction in terms of computational speed. Furthermore, the incremental step avoids the a-priori knowledge of number of sub-classes (which is a necessary parameter in the clustering step of this classification algorithm). Test results show that ICF is, on the average almost 3-times faster than previous versions without sacrificing accuracy. Python 2.7 implementation and software explanations are provided. (C) 2017 Published by Elsevier B.V.