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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| Format: | Conference Paper |
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Institute of Electrical and Electronics Engineers Inc.
2023
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| _version_ | 1833351097496895488 |
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| author | Anuar N.K. Bakar A.A. Ahmad A.R. Yussof S. Rahim F.A. Ramli R. Ismail R. |
| author2 | 57220805366 |
| author_facet | 57220805366 Anuar N.K. Bakar A.A. Ahmad A.R. Yussof S. Rahim F.A. Ramli R. Ismail R. |
| author_sort | Anuar N.K. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| format | Conference Paper |
| id | my.uniten.dspace-25346 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| 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 |
| 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 |
| title | 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_short | Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms |
| title_sort | privacy preserving features selection for data mining using machine learning algorithms |
| url_provider | http://dspace.uniten.edu.my/ |