Cover Image

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

Saved in:
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
Tags: Add Tag
No Tags, Be the first to tag this record!
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
score 13.214268

Similar Items