Cruz, Ricardo , Fernandes, Kelwin , Pinto Costa, Joaquim F. , PÉREZ ORTIZ, MARÍA, Cardoso, Jaime S.

No

Lect. Notes Comput. Sci.

Proceedings Paper

Científica

✗

✗

0.295

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020890344&doi=10.1007%2f978-3-319-59147-6_46&partnerID=40&md5=cf57017926beb556d11e9f331afc8d18

01/01/2017

000443108700046

2-s2.0-85020890344

10.1007/978-3-319-59147-6_46

In classification problems, a dataset is said to be imbalanced when the distribution of the target variable is very unequal. Classes contribute unequally to the decision boundary, and special metrics are used to evaluate these datasets. In previous work, we presented pairwise ranking as a method for binary imbalanced classification, and extended to the ordinal case using weights. In this work, we extend ordinal classification using traditional balancing methods. A comparison is made against traditional and ordinal SVMs, in which the ranking adaption proposed is found to be competitive.

Ordinal classification; Class imbalance; Ranking; SVM