Samat, Nurul Ashikin (2017) An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data. Masters thesis, Universiti Tun Hussein Onn Malaysia.
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Abstract
Data mining techniques are used in various industries, including database marketing, web analysis, information retrieval and bioinformatics to gain a better knowledge extraction. However, if data mining techniques are applied on real datasets, a problem that often comes up is that missing values occur in the datasets. Since the missing values may confuse the data mining process and causing the knowledge extracted unreliable, there is a need to handle the missing values. Therefore, researchers ar.e coming out with imputation methods in the preproce_ssing
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA71-90 Instruments and machines |
| Divisions: | Faculty of Computer Science and Information Technology > Department of Information Security |
| Depositing User: | Mrs. Sabarina Che Mat |
| Date Deposited: | 12 Oct 2022 02:21 |
| Last Modified: | 12 Oct 2022 02:21 |
| URI: | http://eprints.uthm.edu.my/id/eprint/7817 |
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