An ordinal data method for the classification with reject option

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Ricardo Sousa (Author) Other; Beatriz Mora (Author) Other; Jaime S Cardoso (Author) FEUP

Conference proceedings International

Title: EIGHTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS

Pages: 746-750

8th International Conference on Machine Learning and Applications

Miami Beach, FL, DEC 13-15, 2009

Indexing

ISI Web of Knowledge - 6 Citations

ISI Web of Science

Scopus - 10 Citations

INSPEC

Scientific classification

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

Other information

Authenticus ID: P-003-PR9

DOI: 10.1109/icmla.2009.11

Abstract (EN): In this work we consider the problem of binary classification where the classifier may abstain instead of classifying each observation, leaving the critical items for human evaluation. This article motivates and presents a novel method to learn the reject region on complex data. Observations are replicated and then a single binary classifier determines the decision plane. The proposed method is an extension of a method available in the literature for the classification of ordinal data. Our method is compared with standard techniques on synthetic and real datasets, emphasizing the advantages of the proposed approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5