Learning to classify ordinal data: The data replication method

• Type: Article in International Scientific Journal
• Date: 2007

Authors

Jaime S Cardoso (Author) FEUP; Joaquim Pinto P da Costa (Author) FCUP

Journal

Title: Journal of Machine Learning Research

Vol. 8

Pages: 1393-1429

ISSN: 1532-4435

Publisher: MIT Press

Indexing

ISI Web of Knowledge - 114 Citations

ISI Web of Science

Scopus - 146 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Physical sciences > Computer science > Informatics

Other information

Authenticus ID: P-004-94S

Abstract (EN): Classification of ordinal data is one of the most important tasks of relation learning. This paper introduces a new machine learning paradigm specifically intended for classification problems where the classes have a natural order. The technique reduces the problem of classifying ordered classes to the standard two-class problem. The introduced method is then mapped into support vector machines and neural networks. Generalization bounds of the proposed ordinal classifier are also provided. An experimental study with artificial and real data sets, including an application to gene expression analysis, verifies the usefulness of the proposed approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 37