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Introduction to Semi-Supervised Learning

Semi-supervised learning is a machine learning branch that tries to solve problems that include both labeled and unlabeled data, employing concepts that include characteristics of both clustering and classification methods.

The high availability of unlabeled samples, and the difficulty of labeling huge datasets correctly, drove many researchers to investigate the best approaches that allow extending the knowledge provided by the labeled samples to a larger unlabeled population, without loss of accuracy. In this chapter, we're going to introduce this branch of machine learning and we'll discuss:

  • The semi-supervised scenario
  • The different approaches to semi-supervised learning
  • The assumptions needed to ...

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