Journal of Biometrics & Biostatistics

Division of Biostatistics and Population Study, Airlangga University School of Public Health, Surabaya, Indonesia

Publications

• Research   
  K−Nearest Neighbours and K−Fold Cross Validation for Big Data of Covid 19
  Author(s): Kuntoro Kuntoro*
  
  The most popular model in machine learning is K-Nearest Neighbours (KNN). It is used for solving classification. Moreover, K- Fold Crossvalidation is an important tool for assessing the performance of machine learning in doing KNN algorithm given available data. Compared to traditional statistical methods, both algorithms are effective to be implemented in big data. A supervised machine learning approach using KNN and K- Fold Cross- Validation algorithms is implemented in this study. For learning process, data of covid 19 is obtained from website. Four predictors such as new case, reproduction rate, new case in ICU, and hospitalized new case are selected to predict the target, new cases will be alive or will die. After cleaning process, 13,223 of 132,645 data sets are selected. This is considered as original data sets. When K-Fold Cross-Validation is executed b.. Read More»
  DOI: 10.37421/2155-6180.2022.13.145

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