A Survey of Classification Algorithms in Supervised Machine Learning
Author(s):Mageshwari G.¹, Dr. Ramar K.², Monica R. Lakshmi³
Affiliation: 1Assistant Professor, R.M.K. College of Engineering and Technology, 2Professor, R.M.K. College of Engineering and Technology, 3Assistant Professor, R.M.D. Engineering College
Page No: 34-39
Volume issue & Publishing Year: Volume 2 Issue 11 , Nov-2025
Journal: International Journal of Advanced Engineering Application (IJAEA)
ISSN NO: 3048-6807
DOI: https://doi.org/10.5281/zenodo.17753526
Abstract:
Machine learning is crucial in enhancing predictive and diagnostic capabilities across multiple sectors. Professionals can use it to identify potential conditions and assess the risks associated with different intervention strategies. Machine Learning methods have shown significant potential in enhancing disease detection by offering accurate, efficient, and automated diagnostic capabilities. Supervised machine learning is a widely used approach in artificial intelligence that enables systems to learn from labeled data and make accurate predictions. This paper explores various supervised learning techniques, including classification models, which are applied across diverse domains such as healthcare, finance, and natural language processing. This study focuses on the approaches and the applications of supervised learning and highlights its benefits, and discusses ongoing challenges and future directions for improving machine learning-based healthcare solutions.
Keywords: Health Care, Machine Learning, Supervised Learning
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