A Survey on Semi-Supervised Learning Techniques
 | International Journal of ComputerTrends and Technology (IJCTT) |  |
| © 2014 by IJCTT Journal | ||
| Volume-8 Number-1 | ||
| Year of Publication : 2014 | ||
| Authors : V. Jothi Prakash , Dr. L.M. Nithya | ||
| DOI : 10.14445/22312803/IJCTT-V8P105 |
V. Jothi Prakash , Dr. L.M. Nithya. "A Survey on Semi-Supervised Learning Techniques". International Journal of Computer Trends and Technology (IJCTT) 8(1):25-29, February 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Semi-supervised learning is a learning standard which deals with the study of how computers and natural systems such as human beings acquire knowledge in the presence of both labeled and unlabeled data. Semi–supervised learning based methods are preferred when compared to the supervised and unsupervised learning because of the improved performance shown by the semi-supervised approaches in the presence of large volumes of data. Labels are very hard to attain while unlabeled data are surplus, therefore semi-supervised learning is a noble indication to shrink human labor and improve accuracy. There has been a large spectrum of ideas on semi-supervised learning. In this paper we bring out some of the key approaches for semi-supervised learning.
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Keywords semi-supervised learning, generative mixture models, self-training, graph-based models