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Research Article | Open Access |

Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification

Author 1: R. Sathya Author 2: Annamma Abraham
International Journal of Advanced Research in Artificial Intelligence (IJARAI) · Vol. 2, No. 2 · Published 2013 · Cited by 463

DOI: 10.14569/IJARAI.2013.020206

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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

How to Cite this Article

Sathya, R., & Abraham, A. (2013). Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification. International Journal of Advanced Research in Artificial Intelligence, 2(2). https://doi.org/10.14569/IJARAI.2013.020206

Sathya, R., and Annamma Abraham. "Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification." International Journal of Advanced Research in Artificial Intelligence, vol. 2, no. 2, 2013, https://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},
  volume    = {2},
  number    = {2},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {R. Sathya and Annamma Abraham},
  doi       = {10.14569/IJARAI.2013.020206},
  url       = {https://doi.org/10.14569/IJARAI.2013.020206}
}

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