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20 May 2024
Reseach Article

Model based Data Imputation

by Vittanala Sai Bhushan, P. Krishna Subba Rao
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 6
Year of Publication: 2022
Authors: Vittanala Sai Bhushan, P. Krishna Subba Rao
10.5120/ijca2022921894

Vittanala Sai Bhushan, P. Krishna Subba Rao . Model based Data Imputation. International Journal of Computer Applications. 184, 6 ( Apr 2022), 1-4. DOI=10.5120/ijca2022921894

@article{ 10.5120/ijca2022921894,
author = { Vittanala Sai Bhushan, P. Krishna Subba Rao },
title = { Model based Data Imputation },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2022 },
volume = { 184 },
number = { 6 },
month = { Apr },
year = { 2022 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number6/32330-2022921894/ },
doi = { 10.5120/ijca2022921894 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:43.969931+05:30
%A Vittanala Sai Bhushan
%A P. Krishna Subba Rao
%T Model based Data Imputation
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 6
%P 1-4
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Missing or incomplete data is a significant problem in all types of statistical analyses. In this project, multiple imputations using chained equation (MICE) is modified to work with various regression algorithms such as linear regression algorithm. The modified MICE algorithm then will be compared using accuracy on three different datasets.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Imputation MICE Machine learning Multiple Imputation Random Forest.