A comparison of various imputation methods for missing values in air quality data
This paper presents various imputation methods for air quality data specifically in Malaysia. The main objective was to select the best method of imputation and to compare whether there was any difference in the methods used between stations in Peninsular Malaysia. Missing data for various cases are...
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Universiti Kebangsaan Malaysia
2015
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my-ukm.journal.84882016-12-14T06:47:19Z http://journalarticle.ukm.my/8488/ A comparison of various imputation methods for missing values in air quality data Nuryazmin Ahmat Zainuri, Abdul Aziz Jemain, Nora Muda, This paper presents various imputation methods for air quality data specifically in Malaysia. The main objective was to select the best method of imputation and to compare whether there was any difference in the methods used between stations in Peninsular Malaysia. Missing data for various cases are randomly simulated with 5, 10, 15, 20, 25 and 30% missing. Six methods used in this paper were mean and median substitution, expectation-maximization (EM) method, singular value decomposition (SVD), K-nearest neighbour (KNN) method and sequential K-nearest neighbour (SKNN) method. The performance of the imputations is compared using the performance indicator: The correlation coefficient (R), the index of agreement (d) and the mean absolute error (MAE). Based on the result obtained, it can be concluded that EM, KNN and SKNN are the three best methods. The same result are obtained for all the eight monitoring station used in this study. Universiti Kebangsaan Malaysia 2015-03 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/8488/1/17_NuryAzmin.pdf Nuryazmin Ahmat Zainuri, and Abdul Aziz Jemain, and Nora Muda, (2015) A comparison of various imputation methods for missing values in air quality data. Sains Malaysiana, 44 (3). pp. 449-456. ISSN 0126-6039 http://www.ukm.my/jsm/ |
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This paper presents various imputation methods for air quality data specifically in Malaysia. The main objective was to select the best method of imputation and to compare whether there was any difference in the methods used between stations in Peninsular Malaysia. Missing data for various cases are randomly simulated with 5, 10, 15, 20, 25 and 30% missing. Six methods used in this paper were mean and median substitution, expectation-maximization (EM) method, singular value decomposition (SVD), K-nearest neighbour (KNN) method and sequential K-nearest neighbour (SKNN) method. The performance of the imputations is compared using the performance indicator: The correlation coefficient (R), the index of agreement (d) and the mean absolute error (MAE). Based on the result obtained, it can be concluded that EM, KNN and SKNN are the three best methods. The same result are obtained for all the eight monitoring station used in this study. |
| format |
Article |
| author |
Nuryazmin Ahmat Zainuri, Abdul Aziz Jemain, Nora Muda, |
| spellingShingle |
Nuryazmin Ahmat Zainuri, Abdul Aziz Jemain, Nora Muda, A comparison of various imputation methods for missing values in air quality data |
| author_facet |
Nuryazmin Ahmat Zainuri, Abdul Aziz Jemain, Nora Muda, |
| author_sort |
Nuryazmin Ahmat Zainuri, |
| title |
A comparison of various imputation methods for missing
values in air quality data |
| title_short |
A comparison of various imputation methods for missing
values in air quality data |
| title_full |
A comparison of various imputation methods for missing
values in air quality data |
| title_fullStr |
A comparison of various imputation methods for missing
values in air quality data |
| title_full_unstemmed |
A comparison of various imputation methods for missing
values in air quality data |
| title_sort |
comparison of various imputation methods for missing
values in air quality data |
| publisher |
Universiti Kebangsaan Malaysia |
| publishDate |
2015 |
| url |
http://journalarticle.ukm.my/8488/1/17_NuryAzmin.pdf http://journalarticle.ukm.my/8488/ http://www.ukm.my/jsm/ |
| _version_ |
1643737480682274816 |
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13.211869 |