Feature selection for ordinal regression

Stefano Baccianella, Andrea Esuli, Fabrizio Sebastiani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Ordinal regression (also known as ordinal classification) is a supervised learning task that consists of automatically determining the implied rating of a data item on a fixed, discrete rating scale. This problem is receiving increasing attention from the sentiment analysis and opinion mining community, due to the importance of automatically rating increasing amounts of product review data in digital form. As in other supervised learning tasks such as (binary or multiclass) classification, feature selection is needed in order to improve efficiency and to avoid overfitting. However, while feature selection has been extensively studied for other classification tasks, is has not for ordinal regression. In this paper we present four novel feature selection metrics that we have specifically devised for ordinal regression, and test them on two datasets of product review data.

Original languageEnglish
Title of host publicationProceedings of the ACM Symposium on Applied Computing
Pages1748-1754
Number of pages7
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event25th Annual ACM Symposium on Applied Computing, SAC 2010 - Sierre
Duration: 22 Mar 201026 Mar 2010

Other

Other25th Annual ACM Symposium on Applied Computing, SAC 2010
CitySierre
Period22/3/1026/3/10

Fingerprint

Feature extraction
Supervised learning

Keywords

  • feature selection
  • ordinal classification
  • ordinal regression
  • product reviews

ASJC Scopus subject areas

  • Software

Cite this

Baccianella, S., Esuli, A., & Sebastiani, F. (2010). Feature selection for ordinal regression. In Proceedings of the ACM Symposium on Applied Computing (pp. 1748-1754) https://doi.org/10.1145/1774088.1774461

Feature selection for ordinal regression. / Baccianella, Stefano; Esuli, Andrea; Sebastiani, Fabrizio.

Proceedings of the ACM Symposium on Applied Computing. 2010. p. 1748-1754.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Baccianella, S, Esuli, A & Sebastiani, F 2010, Feature selection for ordinal regression. in Proceedings of the ACM Symposium on Applied Computing. pp. 1748-1754, 25th Annual ACM Symposium on Applied Computing, SAC 2010, Sierre, 22/3/10. https://doi.org/10.1145/1774088.1774461
Baccianella S, Esuli A, Sebastiani F. Feature selection for ordinal regression. In Proceedings of the ACM Symposium on Applied Computing. 2010. p. 1748-1754 https://doi.org/10.1145/1774088.1774461
Baccianella, Stefano ; Esuli, Andrea ; Sebastiani, Fabrizio. / Feature selection for ordinal regression. Proceedings of the ACM Symposium on Applied Computing. 2010. pp. 1748-1754
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