A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
A review of various semi-supervised learning models with a deep learning and memory approach
2018
Iran Journal of Computer Science
Based on data types, four learning methods have been presented to extract patterns from data: supervised, semi-supervised, unsupervised, and reinforcement. Regarding machine learning, labeled data are very hard to access, although unlabeled data are usually collected and accessed easily. On the other hand, in most projects, most of the data are unlabeled but some data are labeled. Therefore, semi-supervised learning is more practical and useful for solving most of the problems. Different
doi:10.1007/s42044-018-00027-6
fatcat:nccifurxyzc33fa5xfprrlupxq