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A Tutorial on Hierarchical Classification with Applications in Bioinformatics

Alex Freitas, André Carvalho

Source Title: Research and Trends in Data Mining Technologies and Applications

ISBN13: 9781599042718|ISBN10: 1599042711|EISBN13: 9781599042732

DOI: 10.4018/978-1-59904-271-8.ch007

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MLA

Freitas, Alex, and André Carvalho. "A Tutorial on Hierarchical Classification with Applications in Bioinformatics." Research and Trends in Data Mining Technologies and Applications, edited by David Taniar, IGI Global, 2007, pp. 175-208. https://doi.org/10.4018/978-1-59904-271-8.ch007

APA

Freitas, A. & Carvalho, A. (2007). A Tutorial on Hierarchical Classification with Applications in Bioinformatics. In D. Taniar (Ed.), Research and Trends in Data Mining Technologies and Applications (pp. 175-208). IGI Global. https://doi.org/10.4018/978-1-59904-271-8.ch007

Chicago

Freitas, Alex, and André Carvalho. "A Tutorial on Hierarchical Classification with Applications in Bioinformatics." In Research and Trends in Data Mining Technologies and Applications, edited by David Taniar, 175-208. Hershey, PA: IGI Global, 2007. https://doi.org/10.4018/978-1-59904-271-8.ch007

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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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A Tutorial on Hierarchical Classification with Applications in Bioinformatics

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