primary topic: Missing Values Imputation Using Fuzzy C Means Based on Correlation of Variable
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HTML Summary of #20679 Missing Values Imputation Using Fuzzy C Means Based on Correlation of Variable
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primary topic: Missing Values Imputation Using Fuzzy C Means Based on Correlation of Variable

Missing Values Imputation Using Fuzzy C Means Based on Correlation of Variable
abstract: Missing values is one of the problems in real-world data and an unavoidable one. It should be handled carefully in a pre-processing technique before being processed in a data mining technique. This paper proposes an imputation technique of Fuzzy C Mean (FCM) with the improved version. The aim is to reduce errors and increase the accuracy of the processing technique. In this paper, the correlation technique was applied before the process of FCM to choose the variables with a certain criterion to be processed in FCM imputation. The result shows that the proposed technique outperforms the conventional technique and useful to overcome the disadvantages of the FCM technique. Â© 2020 IEEE.
author list: authors
status: peerReviewed
status: published
date: 2020
is part of: repository
type: AcademicArticle
type: Article
type: ConferenceItemEPrint
type: EPrint

Institute of Electrical and Electronics Engineers Inc.
type: Organization

Farahida Hanim Mausor
family name: Mausor
given name: Farahida Hanim
type: Person

Shakirah Mohd Taib
family name: Taib
given name: Shakirah Mohd
type: Person

Jafreezal Jaafar
family name: Jaafar
given name: Jafreezal
type: Person

2020 International Conference on Computational Intelligence, ICCI 2020
type: Collection