Unsupervised weight parameter estimation method for ensemble learning
type: Item
instance of: scholarly article
title: Unsupervised weight parameter estimation method for ensemble learning
zbMATH Open document ID: 1232.68107
author: Masato Uchida
author: Yousuke Maehara
author: Hiroyuki Shioya
published in: JMMA. Journal of Mathematical Modelling and Algorithms
publication date: 2012-02-21T00:00:00Z
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6008324
zbMATH Keywords: ensemble learning
zbMATH Keywords: unsupervised learning
zbMATH Keywords: exponential mixture model
zbMATH Keywords: Kullback-Leibler divergence
describes a project that uses: AdaBoost.MH
describes a project that uses: UCI-ml
describes a project that uses: SemiBoost
MaRDI profile type: Publication
full work available at URL: s10852-011-9157-1
OpenAlex ID: W2090565762
cites work: Integration of Stochastic Models by Minimizing α-Divergence
cites work: Q4527387
cites work: Bagging predictors
cites work: Q4023085
cites work: A decision-theoretic generalization of on-line learning and an application to boosting
cites work: Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
cites work: Q3260839
cites work: Introduction to Semi-Supervised Learning
DOI: 10.1007/S10852-011-9157-1
description: scientific article; zbMATH DE number 6008324