COMPARISON OF DECISION TREE ALGORITHM AND K-NEAREST NEIGHBOR (KNN) ALGORITHM PERFORMANCE IN DIABETES CASE STUDY
Abstract
Keywords
Full Text:
PDFReferences
Sivanesan, R., Devika, K., & Dhivya, R. (2017). A Review on Diabetes Mellitus diagnoses using classification on Pima Indian Diabetes Data Set. In International Journal of Advance Research in Computer Science and Management Studies (Vol. 5, Issue 1). https://www.academia.edu/35039029/A_Review_on_Diabetes_Mellitus_diagnoses_using_classification_on_Pima_Indian_Diabetes_Data_Set
Mahboob Alam, T., Iqbal, M. A., Ali, Y., Wahab, A., Ijaz, S., Imtiaz Baig, T., Hussain, A., Malik, M. A., Raza, M. M., Ibrar, S., & Abbas, Z. (2019). A model for early prediction of diabetes. Informatics in Medicine Unlocked, 16. https://doi.org/10.1016/j.imu.2019.100204
G. Tripathi and R. Kumar, "Early Prediction of Diabetes Mellitus Using Machine Learning," 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Noida, India, 2020, pp. 1009-1014, doi: 10.1109/ICRITO48877.2020.9197832. https://doi.org/10.1016/j.imu.2019.100204
Alaa Khaleel, F., & Al-Bakry, A. M. (2021). Diagnosis of diabetes using machine learning algorithms. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.07.196
Abedini, M., Bijari, A., & Banirostam, T. (2020). Classification of Pima Indian Diabetes Dataset using Ensemble of Decision Tree, Logistic Regression and Neural Network. IJARCCE, 9(7), 1–4. https://doi.org/10.17148/ijarcce.2020.9701
Karyono, G. (2016). ANALISIS TEKNIK DATA MINING “ALGORITMA C4.5 DAN K-NEAREST NEIGHBOR” UNTUK MENDIAGNOSA PENYAKIT DIABETES MELLITUS. In Seminar Nasional Teknologi Informasi (Vol. 12). http://ojs.palcomtech.ac.id/index.php/SNTIBD/article/view/396
E. K. Hashi, M. S. U. Zaman and M. R. Hasan, "An expert clinical decision support system to predict disease using classification techniques," 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), Cox's Bazar, Bangladesh, 2017, pp. 396-400, doi: 10.1109/ECACE.2017.7912937. https://doi.org/10.1109/ECACE.2017.7912937
Kandhasamy, J. P., & Balamurali, S. (2015). Performance analysis of classifier models to predict diabetes mellitus. Procedia Computer Science, 47(C), 45–51. https://doi.org/10.1016/j.procs.2015.03.182
Sinha, P., & Sinha, P. (2015). Comparative study of chronic kidney disease prediction using KNN and SVM. International Journal of Engineering Research and Technology, 4(12), 608-12. https://www.ijert.org/research/comparative-study-of-chronic-kidney-disease-prediction-using-knn-and-svm-IJERTV4IS120622.pdf
Pranto, B., Mehnaz, S. M., Mahid, E. B., Sadman, I. M., Rahman, A., & Momen, S. (2020). Evaluating machine learning methods for predicting diabetes among female patients in Bangladesh. Information (Switzerland), 11(8). https://doi.org/10.3390/INFO11080374
DOI: https://doi.org/10.24167/proxies.v6i1.12455
Copyright (c) 2024 Proxies : Jurnal Informatika
View My Stats