Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells
Halgamuge, M.N. Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells. Int. J. Environ. Res. Public Health 2020, 17, 4595. https://doi.org/10.3390/ijerph17124595
Halgamuge MN. Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells. International Journal of Environmental Research and Public Health. 2020; 17(12):4595. https://doi.org/10.3390/ijerph17124595
Chicago/Turabian StyleHalgamuge, Malka N. 2020. "Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells" International Journal of Environmental Research and Public Health 17, no. 12: 4595. https://doi.org/10.3390/ijerph17124595