Semi-Supervised Learning Using Procreative Modelling Techniques

Authors

  • Mukund R.
  • John Justin Thangaraj S
  • S P. Chokkalingam

Abstract

Semi-supervised learning could be a learning strategy that investigates how to obtain knowledge before each identified and unlabeled data, like humans, machines and natural systems. Semi-supervised learning-based methods are best appreciated in contrast to controlled due to the improved performance. Labels are terribly disturbing to obtain and unlabeled information is free, but a smart predictor could be semi-supervised leaning to reduce human labor and maximize accuracy.

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Published

2019-12-26

Issue

Section

Articles