A Tutorial on Hierarchical Classification with Applications in Bioinformatics

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Author(s): Alex Freitas (University of Kent, UK)and Andre´ C.P.L.F. de Carvalho (University of São Paulo, Brazil)
Copyright: 2008
Pages: 27
Source title: Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59904-951-9.ch011

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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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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