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Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification
International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 2, 2013.
Abstract: This paper presents a comparative account of unsupervised and supervised learning models and their pattern classification evaluations as applied to the higher education scenario. Classification plays a vital role in machine based learning algorithms and in the present study, we found that, though the error back-propagation learning algorithm as provided by supervised learning model is very efficient for a number of non-linear real-time problems, KSOM of unsupervised learning model, offers efficient solution and classification in the present study.
Keywords: Classification; Clustering; Learning; MLP; SOM; Supervised learning; Unsupervised learning;
R. Sathya and Annamma Abraham. “Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification”. International Journal of Advanced Research in Artificial Intelligence (IJARAI) 2.2 (2013). http://dx.doi.org/10.14569/IJARAI.2013.020206
@article{Sathya2013,
title = {Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.020206},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020206},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {2},
author = {R. Sathya and Annamma Abraham}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
