Hierarchical Feature Selection for Knowledge Discovery
Application of Data Mining to the Biology of Ageing
Authors: Wan, Cen
Free Preview- Discusses the state of the art in hierarchical feature selection algorithms
- Reviews the applications of hierarchical feature selection algorithms to bioinformatics databases
- Surveys the applications of hierarchical feature selection algorithms to research on the biology of ageing
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- About this book
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This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms. The novelties of this book are three-fold. To begin with, this book discusses the hierarchical feature selection in depth, which is generally a novel research area in Data Mining/Machine Learning. Seven different state-of-the-art hierarchical feature selection algorithms are discussed and evaluated by working with four types of interpretable classification algorithms (i.e. three types of Bayesian network classification algorithms and the k-nearest neighbours classification algorithm). Moreover, this book discusses the application of those hierarchical feature selection algorithms on the well-known Gene Ontology database, where the entries (terms) are hierarchically structured. Gene Ontology database that unifies the representations of gene and gene products annotation provides the resource for mining valuable knowledge about certain biological research topics, such as the Biology of Ageing. Furthermore, this book discusses the mined biological patterns by the hierarchical feature selection algorithms relevant to the ageing-associated genes. Those patterns reveal the potential ageing-associated factors that inspire future research directions for the Biology of Ageing research.
- About the authors
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Dr. Cen Wan is a Postdoctoral Research Associate in the Department of Computer Science at University College London, and in the Biomedical Data Science Laboratory at The Francis Crick Institute, London, UK.
- Table of contents (8 chapters)
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Introduction
Pages 1-6
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Data Mining Tasks and Paradigms
Pages 7-15
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Feature Selection Paradigms
Pages 17-23
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Background on Biology of Ageing and Bioinformatics
Pages 25-43
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Lazy Hierarchical Feature Selection
Pages 45-80
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Table of contents (8 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Hierarchical Feature Selection for Knowledge Discovery
- Book Subtitle
- Application of Data Mining to the Biology of Ageing
- Authors
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- Cen Wan
- Series Title
- Advanced Information and Knowledge Processing
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-319-97919-9
- DOI
- 10.1007/978-3-319-97919-9
- Hardcover ISBN
- 978-3-319-97918-2
- Series ISSN
- 1610-3947
- Edition Number
- 1
- Number of Pages
- XIV, 120
- Number of Illustrations
- 29 b/w illustrations, 23 illustrations in colour
- Topics
