Minimum divergence methods in statistical machine learning : from an information geometric viewpoint

Minimum divergence methods in statistical machine learning : from an information geometric viewpoint / Shinto Eguchi, Osamu Komori.

This book explores minimum divergence methods of statistical machine learning for estimation, regression, prediction, and so forth, in which we engage in information geometry to elucidate their intrinsic properties of the corresponding loss functions, learning algorithms, and statistical models. One...

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Bibliographic Details
Main Authors: Eguchi, Shinto (Author), Komori, Osamu (Author)
Format: eBook
Language:English
Published: Tokyo, Japan : Springer, 2022.
Subjects:
Machine learning > Statistical methods.
Aprendizaje automático (Inteligencia artificial) > Métodos estadísticos
Machine learning > Statistical methods
Aprenentatge automàtic.
Estadística matemàtica.
Electronic books.
Llibres electrònics.
Online Access:Click for online access
Table of Contents:
  • Information geometry
  • Information divergence
  • Maximum entropy model
  • Minimum divergence method
  • Unsupervised learning algorithms
  • Regression model
  • Classification. .

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