Kapak Resmi

Minimum Gamma-Divergence for Regression and Classification Problems

This book introduces the gamma-divergence, a measure of distance between probability distributions that was proposed by Fujisawa and Eguchi in 2008. The gamma-divergence has been extensively explored to provide robust estimation when the power index γ is positive. The gamma-divergence can be defined...

Ful tanımlama

Kaydedildi:
Detaylı Bibliyografya
Yazar: Eguchi, Shinto (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: Elektronik Ekitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Edisyon:1st ed. 2025.
Seri Bilgileri:JSS Research Series in Statistics,
Konular:
Statistics .
Stochastic models.
Mathematical statistics.
Machine learning.
Regression analysis.
Biometry.
Statistical Theory and Methods.
Stochastic Modelling in Statistics.
Parametric Inference.
Machine Learning.
Linear Models and Regression.
Biostatistics.
Online Erişim:https://doi.org/10.1007/978-981-97-8880-4
Etiketler: Etiketle
Etiket eklenmemiş, İlk siz ekleyin!
İçindekiler:
  • 1. Introduction
  • 2. Framework of gamma-divergence
  • 2.1. Scale invariance
  • 2.2 GM divergence and HM divergence
  • 3. Minimum divergence methods for generalized linear models
  • 3.1. Bernoulli logistic model
  • 3.2. Poisson log-linear model
  • 3.3. Poisson point process model
  • 4. Minimum divergence methods in machine leaning
  • 4.1. Multi-class AdaBoost
  • 4.2. Boltzmann machine
  • 5. gamma-divergence for real valued functions
  • 6. Discussion.

Benzer Materyaller