Perbandingan Pelbagai Kaedah Imputasi bagi Data Lenyap untuk Data Kualiti Udara

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dc.contributor.authorNuryazmin Ahmat Zainuri
dc.contributor.authorAbdul Aziz Jemain
dc.contributor.authorNora Muda
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-10T03:25:17Z
dc.date.available2024-05-10T03:25:17Z
dc.date.issued2015
dc.description.abstractThis 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).
dc.identifier.citationZainuri, N. A., Jemain, A. A., & Muda, N. (2015). A comparison of various imputation methods for missing values in air quality data. Sains Malaysiana, 44(3), 449-456.
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/536
dc.language.isoen
dc.publisherPenerbit UKM
dc.publisher.alternativeSains Malaysiana
dc.subjectImputation techniques
dc.subjectmissing data
dc.subjectperformance indicators
dc.titlePerbandingan Pelbagai Kaedah Imputasi bagi Data Lenyap untuk Data Kualiti Udara
dc.typeJournal

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