A Uniform Performance Index for Ordinal Classification with Imbalanced Classes

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Wilson Silva (Author) Other; João Ribeiro Pinto (Author) Other; Jaime S. Cardoso (Author) FEUP

Conference proceedings International

Title: Proceedings of the International Joint Conference on Neural Networks

Pages: 1-8

2018 International Joint Conference on Neural Networks, IJCNN 2018

8 July 2018 through 13 July 2018

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

INSPEC

Other information

Authenticus ID: P-00P-SJR

DOI: 10.1109/ijcnn.2018.8489327

Abstract (EN): Ordinal classification is a specific and demanding task, where the aim is not only to increase accuracy, but to also capture the natural order between the classes, and penalize incorrect predictions by how much they deviate from this ranking. If an ordinal classifier must be able to comply with all these requirements, a suitable ordinal metric must be able to accurately measure its degree of compliance. However, the current metrics are unable to completely capture these considerations when assessing classification performance. Moreover, most suffer from sensitivity to imbalanced classes, very common in ordinal classification. In this paper, we propose two variants of a novel performance index that accounts for both accuracy and ranking in the performance assessment of ordinal classification, and is robust against imbalanced classes. © 2018 IEEE.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8