Abstract
Artificial Intelligence, a field which deals with the study and design of systems, which has the capability of observing its environment and does functionalities which aims at maximizing the probability of its success in solving problems. AI turned out to be a field which captured wide interest and attention from the scientific world, so that it gained extraordinary growth. This in turn resulted in the increased focus on a field—which deals with developing the underlying conjectures of learning aspects and learning machines—machine learning. The methodologies and objectives of machine learning played a vital role in the considerable progress gained by AI. Machine learning aims at improving the learning capabilities of intelligent systems. This survey is aimed at providing a theoretical insight into the major algorithms that are used in machine learning and the basic methodology followed in them.
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Acknowledgments
The authors would like to acknowledge Prof. Krishna Shastri (Ex-Joint Director, CIR, Amrita School of Engineering), Sureya Sathiamoorthi and Sree Harini of B.Tech (Computer Science and Engineering), 2010–2014 batch for their support extended in this study. This work was carried out as part of the open-source cloud lab set up by Dr. T. Senthil Kumar, established in Amrita CTS Lab (Amrita Cognizant Innovation Lab) in Amrita School of Engineering, Coimbatore.
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Sankar, A., Divya Bharathi, P., Midhun, M., Vijay, K., Senthil Kumar, T. (2016). A Conjectural Study on Machine Learning Algorithms. In: Suresh, L., Panigrahi, B. (eds) Proceedings of the International Conference on Soft Computing Systems. Advances in Intelligent Systems and Computing, vol 397. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2671-0_10
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DOI: https://doi.org/10.1007/978-81-322-2671-0_10
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