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125559

DATA MINING TECHNIQUES FOR MISSING VALUE IMPUTATION

Article

Last updated: 26 Dec 2024

OverviewSimilar Items

Subjects

-

Tags

Electrical Engineering, Computer Engineering and Electrical power and machines engineering.

Abstract

Imputation is a class of procedures that aims to fill the values which are missed with estimated ones. These methods involve replacing missing values with estimated ones based on some information available in the data set. K-means has been successful in finding missing values for several data sets available such as Bupa, Breast Cancer, Pima, etc. In this paper, we introduce an efficient imputation methods based K-means to treat missing data. Our proposed methods give higher accuracy than the one on given by classical K-means. Experimental results hold on a variety class of data sets.

DOI

10.21608/jesaun.2010.125559

Keywords

Imputation, Clustering, K-mean

Authors

First Name

Marghny H.

Last Name

Mohamed

MiddleName

-

Affiliation

Faculty of computers and Information, Assiut University, Egypt

Email

marghny@aun.edu.eg

City

-

Orcid

-

First Name

Abdel-Rahiem A.

Last Name

Hashem

MiddleName

-

Affiliation

Faculty of Science Assiut University, Egypt

Email

hashem_aer2@yahoo.com

City

-

Orcid

-

First Name

M. M.

Last Name

AbdelSamea

MiddleName

-

Affiliation

Faculty of Science Assiut University, Egypt

Email

-

City

-

Orcid

-

Volume

38

Article Issue

No 4

Related Issue

16876

Issue Date

2010-07-01

Receive Date

2010-06-05

Publish Date

2010-07-01

Page Start

1,001

Page End

1,012

Print ISSN

1687-0530

Online ISSN

2356-8550

Article File

JESAUN_Volume 38_Issue No 4_Pages 1001-1012.pdf

PDF . 684.4kB

Link

https://jesaun.journals.ekb.eg/article_125559.html

Detail API

https://jesaun.journals.ekb.eg/service?article_code=125559

Order

9

Type

Research Paper

Type Code

1,438

Publication Type

Journal

Publication Title

JES. Journal of Engineering Sciences

Publication Link

https://jesaun.journals.ekb.eg/

MainTitle

DATA MINING TECHNIQUES FOR MISSING VALUE IMPUTATION

Details

Type

Article

Created At

23 Jan 2023