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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 117))

Abstract

This chapter introduces the foundations of machine learning that are necessary to motivate its combination to evolutionary algorithms and image processing. In the chapter, we will describe several machine learning tools, suitable for a wide variety of data and tasks. The goal is not to describe the total number of techniques, but instead to present a general view of the field through the description of the mail problems considered in machine learning.

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References

  1. Kramer, O.: Machine Learning for Evolution Strategy. Springer, Switzerland (2016)

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  2. Kevin, P.: Murphy, Machine Learning: A Probabilistic Perspective. MIT Press, London (2011)

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Correspondence to Diego Oliva .

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Oliva, D., Cuevas, E. (2017). An Introduction to Machine Learning. In: Advances and Applications of Optimised Algorithms in Image Processing. Intelligent Systems Reference Library, vol 117. Springer, Cham. https://doi.org/10.1007/978-3-319-48550-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-48550-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48549-2

  • Online ISBN: 978-3-319-48550-8

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