Combining Ranking with Traditional Methods for Ordinal Class Imbalance

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2017

Autores

Cruz, R (Autor) Outra; Fernandes, K (Autor) Outra; Da Costa, JP (Autor) FCUP; Ortiz, MP (Autor) Outra; Jaime S Cardoso (Autor) FEUP

Ata de Conferência Internacional

Título: ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2017, PT II

Páginas: 538-548

14th International Work-Conference on Artificial Neural Networks (IWANN)

Cadiz, SPAIN, JUN 14-16, 2017

Indexação

ISI Web of Knowledge - 6 Citações

Scopus - 9 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Matemática

Outras Informações

ID Authenticus: P-00M-W96

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

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11