Title Combining Ranking with Traditional Methods for Ordinal Class Imbalance
Authors Cruz, Ricardo , Fernandes, Kelwin , Pinto Costa, Joaquim F. , PÉREZ ORTIZ, MARÍA, Cardoso, Jaime S.
External publication No
Means Lect. Notes Comput. Sci.
Scope Proceedings Paper
Nature Científica
JCR Quartile 4
SJR Quartile 2
SJR Impact 0.295
Web 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
Publication date 01/01/2017
ISI 000443108700046
Scopus Id 2-s2.0-85020890344
DOI 10.1007/978-3-319-59147-6_46
Abstract 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.
Keywords Ordinal classification; Class imbalance; Ranking; SVM
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