2df8ed98-e2c0-4c03-9134-85459f600c38 beie director@blueeyesintelligence.org 10.35940/ijitee.J9963.13100924 Fradkin, Dmitriy; Muchnik, Ilya (2006). "Support Vector Machines for Classification" Discrete Methods in Epidemiology. DIMACS Series in Discrete Mathematics and Theoretical Computer Science. Vol. 70. pp. 13-20Ho, Tin Kam (1995). Random Decision Forests Proceedings of the 3rd International Conference on Document Analysis and Recognition, Montreal, QC, 14-16 August 1995.10.1007/BFb0026683Joachims T., "Text categorization with Support Vector Machines: Learning with many relevant features", in Proc. of the European Conference on Machine Learning (ECML), 1998, pages 137-142. https://doi.org/10.1007/BFb002668310.1109/MLSP.2015.7324337K. J. Piczak, "Environmental sound classification with convolutional neural networks," in Proceedings of the IEEE 25th International Workshop on Machine Learning for Signal Processing, 2015, pp. 1-6. https://doi.org/10.1109/MLSP.2015.732433710.1016/j.eswa.2007.01.029Prinzie, A.; Van den Poel, D. (2008). "Random Forests for multiclass classification: Random MultiNomial Logit". Expert Systems with Applications. 34 (3): 1721-1732. https://doi.org/10.1016/j.eswa.2007.01.02910.1001/jama.2016.7653Tolles, Juliana; Meurer, William J (2016). "Logistic Regression Relating Patient Characteristics to Outcomes". JAMA. 316 (5): 533-4. https://doi.org/10.1001/jama.2016.7653Venkatesan, Ragav; Li, Baoxin (2017-10-23). Convolutional Neural Networks in Visual Computing: A Concise Guide. CRC Press. ISBN 978-1-351-65032-8. Archived from the original on 2023-10-16. Retrieved 2020-12-13.https://underthesea.readthedocs.io/en/latest/readme.htmlThegioididong.com10.35940/ijsce.B3557.0512222Sistla, S. (2022). Predicting Diabetes u sing SVM Implemented by Machine Learning. In International Journal of Soft Computing and Engineering (Vol. 12, Issue 2, pp. 16-18). https://doi.org/10.35940/ijsce.b3557.051222210.35940/ijbsac.G0486.039723Muthukrishnan, Dr. R., & Prakash, N. U. (2023). Validate Model Endorsed for Support Vector Machine Alignment with Kernel Function and Depth Concept to Get Superlative Accurateness. In International Journal of Basic Sciences and Applied Computing (Vol. 9, Issue 7, pp. 1-5). https://doi.org/10.35940/ijbsac.g0486.03972310.35940/ijese.K2555.10111123Nagar, K., & Chawla, M. P. S. (2023). A Survey on Various Approaches for Support Vector Machine Based Engineering Applications. In International Journal of Emerging Science and Engineering (Vol. 11, Issue 11, pp. 6-11). https://doi.org/10.35940/ijese.k2555.1011112310.35940/ijitee.J9520.0881019Sharma, D. S. K., & Sharma, M. N. K. (2019). Text Classification Using Ensemble Of Non-Linear Support Vector Machines. In International Journal of Innovative Technology and Exploring Engineering (Vol. 8, Issue 10, pp. 3169-3174). https://doi.org/10.35940/ijitee.j9520.088101910.35940/ijeat.F9377.088619Kumar, C. S., & Thangaraju, P. (2019). Improving Classifier Accuracy for diagnosing Chronic Kidney Disease Using Support Vector Machines. In International Journal of Engineering and Advanced Technology (Vol. 8, Issue 6, pp. 3697-3706). https://doi.org/10.35940/ijeat.f9377.088619