EAN: 9783319979182

HIERARCHICAL FEATURE SELECTION FOR KNOWLEDGE DI...

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.

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