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Authors: Mauri Ferrandin 1 ; Fabrício Enembreck 2 ; Julio César Nievola 2 ; Edson Emílio Scalabrin 2 and Bráulio Coelho Ávila 2

Affiliations: 1 Universidade Federal de Santa Catarina-UFSC, Brazil ; 2 Pontifícia Universidade Católica do Paraná-PUCPR, Brazil

ISBN: 978-989-758-096-3

ISSN: 2184-4992

Keyword(s): Data Mining, Hierarchical Classification, Centroid Classification.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Classification is a common task in Machine Learning and Data Mining. Some classification problems need to take into account a hierarchical taxonomy establishing an order between involved classes and are called hierarchical classification problems. The protein function prediction can be considered a hierarchical classification problem because their functions may be arranged in a hierarchical taxonomy of classes. This paper presents an algorithm for hierarchical classification using a centroid-based approach with two versions named HCCS and HCCSic respectively. Centroid-based techniques have been widely used to text classification and in this work we explore it’s adoption to a hierarchical classification scenario. The proposed algorithm was evaluated in eight real datasets and compared against two other recent algorithms from the literature. Preliminary results showed that the proposed approach is an alternative for hierarchical classification, having as main advantage the simplicity an d low computational complexity with good accuracy. (More)

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Paper citation in several formats:
Ferrandin, M.; Enembreck, F.; Nievola, J.; Scalabrin, E. and Ávila, B. (2015). A Centroid-based Approach for Hierarchical Classification.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-096-3, ISSN 2184-4992, pages 25-33. DOI: 10.5220/0005339000250033

author={Mauri Ferrandin. and Fabrício Enembreck. and Julio César Nievola. and Edson Emílio Scalabrin. and Bráulio Coelho Ávila.},
title={A Centroid-based Approach for Hierarchical Classification},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},


JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A Centroid-based Approach for Hierarchical Classification
SN - 978-989-758-096-3
AU - Ferrandin, M.
AU - Enembreck, F.
AU - Nievola, J.
AU - Scalabrin, E.
AU - Ávila, B.
PY - 2015
SP - 25
EP - 33
DO - 10.5220/0005339000250033

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