Semi-supervised learning
The Semi-Supervised Learning (SSL) paradigm is an extension of supervised learning with the principle of inclusion of unlabeled in- stances, which are used as background knowledge. When using SSL for a classification task, the entire approach is usually denoted as a Semi-Supervised Classification (SSC) ( Chapelle et al., 2010 ), where unlabeled data can be…