Publication:
Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms

Simple item page
dc.citedby2
dc.contributor.authorAnuar N.K.en_US
dc.contributor.authorBakar A.A.en_US
dc.contributor.authorAhmad A.R.en_US
dc.contributor.authorYussof S.en_US
dc.contributor.authorRahim F.A.en_US
dc.contributor.authorRamli R.en_US
dc.contributor.authorIsmail R.en_US
dc.contributor.authorid57220805366en_US
dc.contributor.authorid35178991300en_US
dc.contributor.authorid35589598800en_US
dc.contributor.authorid16023225600en_US
dc.contributor.authorid57350579500en_US
dc.contributor.authorid57191413657en_US
dc.contributor.authorid15839357700en_US
dc.date.accessioned2023-05-29T08:08:23Z
dc.date.available2023-05-29T08:08:23Z
dc.date.issued2020
dc.descriptionData 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 algorithmsen_US
dc.description.abstractFeatures 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9243355
dc.identifier.doi10.1109/ICIMU49871.2020.9243355
dc.identifier.epage113
dc.identifier.scopus2-s2.0-85097641211
dc.identifier.spage108
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097641211&doi=10.1109%2fICIMU49871.2020.9243355&partnerID=40&md5=48f4109f668ca8523079dbc50ad8194e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25346
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2020 8th International Conference on Information Technology and Multimedia, ICIMU 2020
dc.titlePrivacy Preserving Features Selection for Data Mining using Machine Learning Algorithmsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
Files
Collections
SCOPUS