Visual Analytics and Human Involvement in Machine Learning

Salomon Eisler, Joachim Meyer*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationMachine Learning for Data Science Handbook
Subtitle of host publicationData Mining and Knowledge Discovery Handbook, Third Edition
PublisherSpringer International Publishing
Pages945-970
Number of pages26
ISBN (Electronic)9783031246289
ISBN (Print)9783031246272
DOIs
StatePublished - 1 Jan 2023

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