Supervised learning : mathematical foundations and real-world applications /

"This book discusses the relevance of probabilistic supervised learning, to the pursuit of automated and reliable prediction of an unknown that is in a state of relationship with another variable. The book provides methods for secured mechanistic learning of the function that represents this re...

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Bibliographic Details
Main Author:	Chakrabarty, Dalia (Author)
Format:	eBook
Language:	English
Published:	Boca Raton, FL : CRC Press, 2025.
Edition:	First edition.
Subjects:	Supervised learning (Machine learning) Supervised learning (Machine learning) > Mathematical models. Apprentissage supervisé (Intelligence artificielle) Apprentissage supervisé (Intelligence artificielle) > Modèles mathématiques.

Table of Contents:

Foreword Preface Acknowledgements 1. Inter-variable relationships 2. Bayesianism 3. Supervised learning & prediction, using Gaussian Processes 4. Covariance kernels suitable for real-world data 5. Learning a high-dimensional function 6. A self-assembled prior on correlation matrices Bibliography Index