Mathematical foundations for supervised learning

Mark Hoogendoorn; Burkhardt Funk

doi:10.1007/978-3-319-66308-1_6

Mathematical foundations for supervised learning

Mark Hoogendoorn^*, Burkhardt Funk

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

Abstract

In this chapter the theoretical underpinning of supervised learning are discussed. The whole supervised machine learning process is explained from a more formal perspective as well as some underlying theories. The theories discussed include concepts such as PAC learnability and VC dimensions. The implications of these theories are discussed.

Original language	English
Title of host publication	Machine Learning or the Quantiﬁed Self
Subtitle of host publication	On the Art of Learning from Sensory Data
Publisher	Springer/Verlag
Chapter	6
Pages	101-121
Number of pages	21
Volume	35
ISBN (Electronic)	9783319663081
ISBN (Print)	9783319663074
DOIs	https://doi.org/10.1007/978-3-319-66308-1_6
Publication status	Published - 2018

Publication series

Name	Cognitive Systems Monographs
Volume	35
ISSN (Print)	1867-4925
ISSN (Electronic)	1867-4933

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title = "Mathematical foundations for supervised learning",

abstract = "In this chapter the theoretical underpinning of supervised learning are discussed. The whole supervised machine learning process is explained from a more formal perspective as well as some underlying theories. The theories discussed include concepts such as PAC learnability and VC dimensions. The implications of these theories are discussed.",

author = "Mark Hoogendoorn and Burkhardt Funk",

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BT - Machine Learning or the Quantiﬁed Self

PB - Springer/Verlag

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Mathematical foundations for supervised learning

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