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A Tutorial on Hierarchical Classification with Applications in Bioinformatics

A Tutorial on Hierarchical Classification with Applications in Bioinformatics

Alex Freitas, Andre´ C.P.L.F. de Carvalho
Copyright: © 2008 |Pages: 27
ISBN13: 9781599049519|ISBN10: 1599049511|EISBN13: 9781599049526
DOI: 10.4018/978-1-59904-951-9.ch011
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MLA

Freitas, Alex, and Andre´ C.P.L.F. de Carvalho. "A Tutorial on Hierarchical Classification with Applications in Bioinformatics." Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, IGI Global, 2008, pp. 119-145. https://doi.org/10.4018/978-1-59904-951-9.ch011

APA

Freitas, A. & de Carvalho, A. C. (2008). A Tutorial on Hierarchical Classification with Applications in Bioinformatics. In J. Wang (Ed.), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (pp. 119-145). IGI Global. https://doi.org/10.4018/978-1-59904-951-9.ch011

Chicago

Freitas, Alex, and Andre´ C.P.L.F. de Carvalho. "A Tutorial on Hierarchical Classification with Applications in Bioinformatics." In Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, 119-145. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-951-9.ch011

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Abstract

In machine learning and data mining, most of the works in classification problems deal with flat classification, where each instance is classified in one of a set of possible classes and there is no hierarchical relationship between the classes. There are, however, more complex classification problems where the classes to be predicted are hierarchically related. This chapter presents a tutorial on the hierarchical classification techniques found in the literature. We also discuss how hierarchical classification techniques have been applied to the area of bioinformatics (particularly the prediction of protein function), where hierarchical classification problems are often found.

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