Mathematical foundations for supervised learning

Mark Hoogendoorn, Burkhardt Funk

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-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 languageEnglish
Title of host publicationMachine Learning or the Quantified Self
Subtitle of host publicationOn the Art of Learning from Sensory Data
PublisherSpringer/Verlag
Chapter6
Pages101-121
Number of pages21
Volume35
ISBN (Electronic)9783319663081
ISBN (Print)9783319663074
DOIs
Publication statusE-pub ahead of print - 27 Sep 2017

Publication series

NameCognitive Systems Monographs
Volume35
ISSN (Print)1867-4925
ISSN (Electronic)1867-4933

Fingerprint

Supervised learning
Learning systems

Cite this

Hoogendoorn, M., & Funk, B. (2017). Mathematical foundations for supervised learning. In Machine Learning or the Quantified Self: On the Art of Learning from Sensory Data (Vol. 35, pp. 101-121). (Cognitive Systems Monographs; Vol. 35). Springer/Verlag. https://doi.org/10.1007/978-3-319-66308-1_6
Hoogendoorn, Mark ; Funk, Burkhardt. / Mathematical foundations for supervised learning. Machine Learning or the Quantified Self: On the Art of Learning from Sensory Data. Vol. 35 Springer/Verlag, 2017. pp. 101-121 (Cognitive Systems Monographs).
@inbook{8af870b814f94ad194d84c6a6c1d22c9,
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",
year = "2017",
month = "9",
day = "27",
doi = "10.1007/978-3-319-66308-1_6",
language = "English",
isbn = "9783319663074",
volume = "35",
series = "Cognitive Systems Monographs",
publisher = "Springer/Verlag",
pages = "101--121",
booktitle = "Machine Learning or the Quantified Self",

}

Hoogendoorn, M & Funk, B 2017, Mathematical foundations for supervised learning. in Machine Learning or the Quantified Self: On the Art of Learning from Sensory Data. vol. 35, Cognitive Systems Monographs, vol. 35, Springer/Verlag, pp. 101-121. https://doi.org/10.1007/978-3-319-66308-1_6

Mathematical foundations for supervised learning. / Hoogendoorn, Mark; Funk, Burkhardt.

Machine Learning or the Quantified Self: On the Art of Learning from Sensory Data. Vol. 35 Springer/Verlag, 2017. p. 101-121 (Cognitive Systems Monographs; Vol. 35).

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

TY - CHAP

T1 - Mathematical foundations for supervised learning

AU - Hoogendoorn, Mark

AU - Funk, Burkhardt

PY - 2017/9/27

Y1 - 2017/9/27

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85030716950&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85030716950&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-66308-1_6

DO - 10.1007/978-3-319-66308-1_6

M3 - Chapter

SN - 9783319663074

VL - 35

T3 - Cognitive Systems Monographs

SP - 101

EP - 121

BT - Machine Learning or the Quantified Self

PB - Springer/Verlag

ER -

Hoogendoorn M, Funk B. Mathematical foundations for supervised learning. In Machine Learning or the Quantified Self: On the Art of Learning from Sensory Data. Vol. 35. Springer/Verlag. 2017. p. 101-121. (Cognitive Systems Monographs). https://doi.org/10.1007/978-3-319-66308-1_6