# MULTI-CLASS FROM BINARY - Divide to conquer

### Anderson Rocha, Siome Goldenstein

#### 2009

#### Abstract

Several researchers have proposed effective approaches for binary classification in the last years. We can easily extend some of those techniques to multi-class. Notwithstanding, some other powerful classifiers (e.g., SVMs) are hard to extend to multi-class. In such cases, the usual approach is to reduce the multi-class problem complexity into simpler binary classification problems (divide-and-conquer). In this paper, we address the multi-class problem by introducing the concept of affine relations among binary classifiers (dichotomies), and present a principled way to find groups of high correlated base learners. Finally, we devise a strategy to reduce the number of required dichotomies in the overall multi-class process.

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#### Paper Citation

#### in Harvard Style

Rocha A. and Goldenstein S. (2009). **MULTI-CLASS FROM BINARY - Divide to conquer** . In *Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)* ISBN 978-989-8111-69-2, pages 323-330. DOI: 10.5220/0001777803230330

#### in Bibtex Style

@conference{visapp09,

author={Anderson Rocha and Siome Goldenstein},

title={MULTI-CLASS FROM BINARY - Divide to conquer},

booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)},

year={2009},

pages={323-330},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0001777803230330},

isbn={978-989-8111-69-2},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)

TI - MULTI-CLASS FROM BINARY - Divide to conquer

SN - 978-989-8111-69-2

AU - Rocha A.

AU - Goldenstein S.

PY - 2009

SP - 323

EP - 330

DO - 10.5220/0001777803230330