Missing values imputation tool using imputex algorithm
Missing data is a prevalent issue affecting data quality across numerous fields. One frequent challenge arises when data is lost during the input stage. Numerous studies have proposed methods to impute missing values for data across multiple fields. However, certain domains present unique challenges...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Manash Kozybayev North Kazakhstan University
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/118068/ http://psasir.upm.edu.my/id/eprint/118068/1/118068.pdf |
| _version_ | 1848867421083926528 |
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| author | Sidi, Fatimah Abdullah, Lili Nurliyana Alabadla, Mustafa Ishak, Iskandar |
| author_facet | Sidi, Fatimah Abdullah, Lili Nurliyana Alabadla, Mustafa Ishak, Iskandar |
| author_sort | Sidi, Fatimah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Missing data is a prevalent issue affecting data quality across numerous fields. One frequent challenge arises when data is lost during the input stage. Numerous studies have proposed methods to impute missing values for data across multiple fields. However, certain domains present unique challenges due to the involvement of attributes from multiple scientific disciplines, such as biology, chemistry, and medical which complicates the imputation process. The purpose of this study is to design an application that addresses missing values and maintains accuracy in large datasets, with a focus on minimizing processing time. The application's performance is evaluated based on classification accuracy using various imputation methods. The proposed application outperforms performance compared to current software tools such as against R package, Statistical Package for the Social Sciences (SPSS), Stata, and Microsoft Excel. This study helps to improve data quality and contributes to data science by improving the data cleaning procedure, which is a step in the data pre-processing stage. |
| first_indexed | 2025-11-15T14:36:13Z |
| format | Article |
| id | upm-118068 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:36:13Z |
| publishDate | 2024 |
| publisher | Manash Kozybayev North Kazakhstan University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1180682025-06-24T00:28:23Z http://psasir.upm.edu.my/id/eprint/118068/ Missing values imputation tool using imputex algorithm Sidi, Fatimah Abdullah, Lili Nurliyana Alabadla, Mustafa Ishak, Iskandar Missing data is a prevalent issue affecting data quality across numerous fields. One frequent challenge arises when data is lost during the input stage. Numerous studies have proposed methods to impute missing values for data across multiple fields. However, certain domains present unique challenges due to the involvement of attributes from multiple scientific disciplines, such as biology, chemistry, and medical which complicates the imputation process. The purpose of this study is to design an application that addresses missing values and maintains accuracy in large datasets, with a focus on minimizing processing time. The application's performance is evaluated based on classification accuracy using various imputation methods. The proposed application outperforms performance compared to current software tools such as against R package, Statistical Package for the Social Sciences (SPSS), Stata, and Microsoft Excel. This study helps to improve data quality and contributes to data science by improving the data cleaning procedure, which is a step in the data pre-processing stage. Manash Kozybayev North Kazakhstan University 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/118068/1/118068.pdf Sidi, Fatimah and Abdullah, Lili Nurliyana and Alabadla, Mustafa and Ishak, Iskandar (2024) Missing values imputation tool using imputex algorithm. Vestnik of M. Kozybayev North Kazakhstan University, 4 (64). pp. 195-203. ISSN 2958-003X; eISSN; 2958-0048 https://vestnik.ku.edu.kz/jour/article/view/1916 10.54596/2958-0048-2024-4-195-203 |
| spellingShingle | Sidi, Fatimah Abdullah, Lili Nurliyana Alabadla, Mustafa Ishak, Iskandar Missing values imputation tool using imputex algorithm |
| title | Missing values imputation tool using imputex algorithm |
| title_full | Missing values imputation tool using imputex algorithm |
| title_fullStr | Missing values imputation tool using imputex algorithm |
| title_full_unstemmed | Missing values imputation tool using imputex algorithm |
| title_short | Missing values imputation tool using imputex algorithm |
| title_sort | missing values imputation tool using imputex algorithm |
| url | http://psasir.upm.edu.my/id/eprint/118068/ http://psasir.upm.edu.my/id/eprint/118068/ http://psasir.upm.edu.my/id/eprint/118068/ http://psasir.upm.edu.my/id/eprint/118068/1/118068.pdf |