A review on feature selection algorithms
subject: Classification; Feature selection; Genetic algorithm; Wrapper method
description: A large number of data are increasing in multiple fields such as social media, bioinformatics and health care. These data contain redundant, irrelevant or noisy data which causes high dimensionality. Feature selection is generally used in data mining to define the tools and techniques available for reducing inputs to a controllable size for processing and analysis. Feature selection is also used for dimension reduction, machine learning and other data mining applications. A survey of different feature selection methods are presented in this paper for obtaining relevant features. It also introduces feature selection algorithm called genetic algorithm for detection and diagnosis of biological problems. Genetic algorithm is mainly focused in the field of medicines which can be beneficial for physicians to solve complex problems. Finally, this paper concludes with various challenges and applications in feature selection. Springer Nature Singapore Pte Ltd 2019.
creator: Colaco S.; Kumar S.; Tamang A.; Biju V.G.
source: Advances in Intelligent Systems and Computing, Vol-906, pp. 133-153.
publisher: Springer Verlag
date: 2019-01-01
rights: Restricted Access
relation: ISSN: 21945357; ISBN: 978-981136000-8
format: Online
language: English
type: Conference paper
coverage: Colaco S., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India; Kumar S., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India; Tamang A., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India; Biju V.G., Department of CSE, Christ(Deemed to Be University), Bangalore, 560029, India