Investigation of the Role of Test Size, Random State, and Dataset in the Accuracy of Classification Algorithms
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-2100-3_55
Reference23 articles.
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2. Uçar MK, Nour M, Sindi H, Polat K (2020) The effect of training and testing process on machine learning in biomedical datasets. Math Probl Eng 2020. https://doi.org/10.1155/2020/2836236
3. Althnian A, AlSaeed D, Al-Baity H, Samha A, Dris A bin, Alzakari N, Abou Elwafa A, Kurdi H (2021) Impact of dataset size on classification performance: an empirical evaluation in the medical domain. Appl Sci (Switzerland). 11. https://doi.org/10.3390/app11020796
4. Prusa J, Khoshgoftaar TM, Seliya N (2016) The effect of dataset size on training tweet sentiment classifiers. In: Proceedings—2015 IEEE 14th international conference on machine learning and applications, ICMLA 2015. https://doi.org/10.1109/ICMLA.2015.22
5. Obuchowski NA (1998) Sample size calculations in studies of test accuracy. https://doi.org/10.1177/096228029800700405
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