CINXE.COM

{"title":"Unveiling the Mathematical Essence of Machine Learning: A Comprehensive Exploration","authors":"Randhir Singh Baghel","volume":209,"journal":"International Journal of Mathematical and Computational Sciences","pagesStart":52,"pagesEnd":60,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10013634","abstract":"<p>In this study, the fundamental ideas guiding the dynamic area of machine learning\u2014where models thrive and algorithms change over time\u2014are rooted in an innate mathematical link. This study explores the fundamental ideas that drive the development of intelligent systems, providing light on the mutually beneficial link between mathematics and machine learning.<\/p>","references":"[1]\tAli, Abdulalem, Shukor Abd Razak, Siti Hajar Othman, Taiseer Abdalla Elfadil Eisa, Arafat Al-Dhaqm, Maged Nasser, Tusneem Elhassan, Hashim Elshafie, and Abdu Saif. 2022. Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review. 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Chaudhary, R.S. Baghel and A.C. Pandey, 2015 \u201cMathematical Modelling and Estimation of Seasonal Variation of Mosquito Population: A Real Case Study,\u201d Bol. Soc. Paran. Mat., vol. 33 2 (2015): 165\u2013176.\r\n[31]\tO.P. Misra, R. S. Baghel, M. Chaudhary and J.Dhar, 2015 \u201cSpatiotemporal based predator-prey harvesting model for fishery with Beddington-Deangelis type functional response and tax as the control entity,\u201d Dynamics of Continuous, Discrete and Impulsive Systems Series A., vol. 26 2 (2019): 113--135.\r\n[32]\tS. 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Zhang, Short-Term Wind Power Forecasting on Multiple Scales Using VMD Decomposition, K-Means Clustering and LSTM Principal Computing, IEEE Access 7 (2019) 166917\u2013166929,\r\n[47]\thttps:\/\/hkrtrainings.com\/classifications-in-machine-learning","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 209, 2024"}