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Visual Analytics and Human Involvement in Machine Learning

In: Machine Learning for Data Science Handbook

Author

Listed:
  • Salomon Eisler

    (Tel Aviv University)

  • Joachim Meyer

    (Tel Aviv University)

Abstract

The rapidly developing AI systems and applications still require human involvement in practically all parts of the analytics process. Human decisions are largely based on visualizations, providing data scientists with details of data properties and the results of analytical procedures. Different visualizations are used in the different steps of the machine learning (ML) process. The decision on which visualization to use depends on factors, such as the data domain, the data model, and the step in the ML process. In this chapter, we describe the seven steps in the ML process and review different visualization techniques that are relevant for the different steps for different types of data, models, and purposes.

Suggested Citation

  • Salomon Eisler & Joachim Meyer, 2023. "Visual Analytics and Human Involvement in Machine Learning," Springer Books, in: Lior Rokach & Oded Maimon & Erez Shmueli (ed.), Machine Learning for Data Science Handbook, edition 0, pages 945-970, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-24628-9_40
    DOI: 10.1007/978-3-031-24628-9_40
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