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E-book
Author Wan, Cen, author

Title Hierarchical feature selection for knowledge discovery : application of data mining to the biology of ageing / Cen Wan
Published Cham, Switzerland : Springer, [2019]
©2019

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Description 1 online resource
Series Advanced information and knowledge processing
Advanced information and knowledge processing.
Contents Introduction -- Data Mining Tasks and Paradigms -- Feature Selection Paradigms -- Background on Biology of Ageing and Bioinformatics -- Lazy Hierarchical Feature Selection -- Eager Hierarchical Feature Selection -- Comparison of Lazy and Eager Hierarchical Feature Selection Methods and Biological Interpretation on Frequently Selected Gene Ontology Terms Relevant to the Biology of Ageing -- Conclusions and Research Directions
Summary 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
Bibliography Includes bibliographical references and index
Notes Vendor-supplied metadata
Subject Aging.
Data mining.
Aging
Data Mining
SCIENCE -- Life Sciences -- Anatomy & Physiology.
Aging
Data mining
Form Electronic book
ISBN 9783319979199
3319979191
3319979183
9783319979182
9783319979205
3319979205