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Binary Credal Classification Under Sparsity Constraints

Basu, Tathagata; Troffaes, Matthias C.M.; Einbeck, Jochen

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Authors

Tathagata Basu



Contributors

Marie-Jeanne Lesot
Editor

Susana Vieira
Editor

Marek Z. Reformat
Editor

Joao Paulo Carvalho
Editor

Anna Wilbik
Editor

Bernadette Bouchon-Meunier
Editor

Ronald R. Yager
Editor

Abstract

Binary classification is a well known problem in statistics. Besides classical methods, several techniques such as the naive credal classifier (for categorical data) and imprecise logistic regression (for continuous data) have been proposed to handle sparse data. However, a convincing approach to the classification problem in high dimensional problems (i.e., when the number of attributes is larger than the number of observations) is yet to be explored in the context of imprecise probability. In this article, we propose a sensitivity analysis based on penalised logistic regression scheme that works as binary classifier for high dimensional cases. We use an approach based on a set of likelihood functions (i.e. an imprecise likelihood, if you like), that assigns a set of weights to the attributes, to ensure a robust selection of the important attributes, whilst training the model at the same time, all in one fell swoop. We do a sensitivity analysis on the weights of the penalty term resulting in a set of sparse constraints which helps to identify imprecision in the dataset.

Citation

Basu, T., Troffaes, M. C., & Einbeck, J. (2020). Binary Credal Classification Under Sparsity Constraints. In M. Lesot, S. Vieira, M. Z. Reformat, J. P. Carvalho, A. Wilbik, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information processing and management of uncertainty in knowledge-based systems : 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15–19, 2020, proceedings, Part II (82-95). https://doi.org/10.1007/978-3-030-50143-3_7

Conference Name Information Processing and Management of Uncertainty in Knowledge-Based Systems
Conference Location Lisbon
Acceptance Date Mar 18, 2020
Online Publication Date Jun 5, 2020
Publication Date 2020
Deposit Date Jun 7, 2020
Publicly Available Date Jun 5, 2021
Pages 82-95
Series ISSN 1865-0929,1865-0937
Book Title Information processing and management of uncertainty in knowledge-based systems : 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15–19, 2020, proceedings, Part II.
ISBN 9783030501426
DOI https://doi.org/10.1007/978-3-030-50143-3_7
Public URL https://durham-repository.worktribe.com/output/1142528

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Copyright Statement
This is a post-peer-review, pre-copyedit version of an book chapter published in Information processing and management of uncertainty in knowledge-based systems : 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15–19, 2020, proceedings, Part II. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-50143-3_7





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