Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms

Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms

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Bibliographic Details
Main Authors:	Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.
Other Authors:	57220805366
Format:	Conference Paper
Published:	Institute of Electrical and Electronics Engineers Inc. 2023
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Institution:	Universiti Tenaga Nasional

id	my.uniten.dspace-25346
record_format	dspace
spelling	my.uniten.dspace-253462023-05-29T16:08:23Z Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms Anuar N.K. Bakar A.A. Ahmad A.R. Yussof S. Rahim F.A. Ramli R. Ismail R. 57220805366 35178991300 35589598800 16023225600 57350579500 57191413657 15839357700 Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms Features selection known as process of lessening the number of inputs while designing a predictive model using machine learning algorithms. Metadata is an asset because useful information is concealing in these large quantities of data. Data analytics needs more in-depth insight and the identification of fine-grain patterns to make precise predictions that allow better decision-making. To make identification towards the data, the privacy of the data must be preserving. It will ensure there is no leakage information to other parties. In this paper, we review features selection for data mining and machine learning algorithms to preserve data privacy. � 2020 IEEE. Final 2023-05-29T08:08:23Z 2023-05-29T08:08:23Z 2020 Conference Paper 10.1109/ICIMU49871.2020.9243355 2-s2.0-85097641211 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097641211&doi=10.1109%2fICIMU49871.2020.9243355&partnerID=40&md5=48f4109f668ca8523079dbc50ad8194e https://irepository.uniten.edu.my/handle/123456789/25346 9243355 108 113 Institute of Electrical and Electronics Engineers Inc. Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
description	Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms
author2	57220805366
author_facet	57220805366 Anuar N.K. Bakar A.A. Ahmad A.R. Yussof S. Rahim F.A. Ramli R. Ismail R.
format	Conference Paper
author	Anuar N.K. Bakar A.A. Ahmad A.R. Yussof S. Rahim F.A. Ramli R. Ismail R.
spellingShingle	Anuar N.K. Bakar A.A. Ahmad A.R. Yussof S. Rahim F.A. Ramli R. Ismail R. Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
author_sort	Anuar N.K.
title	Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
title_short	Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
title_full	Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
title_fullStr	Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
title_full_unstemmed	Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
title_sort	privacy preserving features selection for data mining using machine learning algorithms
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2023
_version_	1806424674265989120

Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms

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