Description
Hierarchical Feature Selection for Knowledge Discovery, 1st ed. 2019
Application of Data Mining to the Biology of Ageing
Advanced Information and Knowledge Processing Series
Author: Wan Cen
Language: EnglishSubject for Hierarchical Feature Selection for Knowledge Discovery:
120 p. · 15.5x23.5 cm · Hardback
Description
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/li>Biography
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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
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.
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