Missing data characteristics and the choice of imputation technique: an empirical study
One important characteristic of good data is completeness. Missing data is a major problem in the classification of medical datasets. It leads to incorrect classification of patients, which is dangerous to health management of patients. Many imputation techniques have been employed to solve this pro...
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| 主要な著者: | , , , |
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| フォーマット: | Conference or Workshop Item |
| 出版事項: |
2020
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/id/eprint/93785/ http://dx.doi.org/10.1007/978-3-030-33582-3_9 |
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