On the goodness of fit of parametric and non-parametric data mining techniques: the case of malaria incidence thresholds in Uganda-Reference-Cited by-同舟云学术

On the goodness of fit of parametric and non-parametric data mining techniques: the case of malaria incidence thresholds in Uganda

Published:2021-04-21 Issue:4 Volume:11 Page:929-940
ISSN:2190-7188
Container-title:Health and Technology
language:en
Short-container-title:Health Technol.

Author:

Bbosa Francis Fuller^ORCID,Nabukenya Josephine,Nabende Peter,Wesonga Ronald

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://link.springer.com/content/pdf/10.1007/s12553-021-00551-9.pdf

Reference110 articles.

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4. Olayinka TC, Chiemeke SC. Predicting paediatric malaria occurrence using classification algorithm in data mining. J Adv Math Comput Sci. 2019;31(4):1–10. https://doi.org/10.9734/JAMCS/2019/v31i430118.

5. Hagenauer J, Omrani H, Helbich M. Assessing the performance of 38 machine learning models : the case of land consumption rates in Bavaria, Germany. Int J Geogr Inf Sci. 2019;1–21. https://doi.org/10.1080/13658816.2019.1579333.

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