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A global-model naive Bayes approach to the hierarchical prediction of protein functions

Silla Jr, Carlos N. and Freitas, Alex A. (2009) A global-model naive Bayes approach to the hierarchical prediction of protein functions. In: Wang, Wei and Kargupta, Hillol and Ranka, Sanjay and Yu, Philip S. and Wu, Xindong, eds. 2009 Ninth IEEE International Conference on Data Mining. IEEE, pp. 182-196. ISBN 978-1-4244-5242-2. (doi:10.1109/ICDM.2009.85) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/ICDM.2009.85

Abstract

In this paper we propose a new global-model approach for hierarchical classification, where a single global classification model is built by considering all the classes in the hierarchy - rather than building a number of local classification models as it is more usual in hierarchical classification. The method is an extension of the flat classification algorithm naive Bayes. We present the extension made to the original algorithm as well as its evaluation on eight protein function hierarchical classification datasets. The achieved results are positive and show that the proposed global model is better than using a local model approach.

Item Type: Book section
DOI/Identification number: 10.1109/ICDM.2009.85
Uncontrolled keywords: determinacy analysis; Craig interpolants; proteins; classification algorithms; machine learning algorithms; testing; predictive models; bioinformatics; classification tree analysis; data mining; biomedical computing; biomedical informatics
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: C.N. Silla-Junior
Date Deposited: 21 Sep 2012 09:49 UTC
Last Modified: 04 Feb 2020 04:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/30573 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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