Wan, Cen and Freitas, A. (2016) A new hierarchical redundancy eliminated tree augmented naive Bayes classifier for coping with gene ontology-based features. In: The 33rd International Conference on Machine Learning (ICML) Workshop on Computational Biology, 24th June 2016, New York.
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Abstract
The Tree Augmented Naive Bayes classifier is a type of probabilistic graphical model that can represent some feature dependencies. In this work, we propose a Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes (HRE–TAN) algorithm, which considers removing the hierarchical redundancy during the classifier learning process, when coping with data containing hierarchically structured features. The experiments showed that HRE–TAN obtains significantly better predictive performance than the conventional Tree Augmented Naive Bayes classifier, and enhanced the robustness against imbalanced class distributions, in aging-related gene datasets with Gene Ontology terms used as features.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Published on arXiv: https://arxiv.org/pdf/1607.01690.pdf |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Bioinformatics, Bloomsbury Centre for (Closed) |
| Depositing User: | Cen Wan |
| Date Deposited: | 09 May 2022 17:43 |
| Last Modified: | 09 Aug 2023 12:47 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/30715 |
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