Adaptive covariate acquisition for minimizing total cost of classification
type: Item
instance of: scholarly article
title: Adaptive covariate acquisition for minimizing total cost of classification
author: Daniel Andrade
author: Yuzuru Okajima
published in: Machine Learning
publication date: 2021-11-24T00:00:00Z
full work available at URL: https://arxiv.org/abs/2002.09162
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7432830
zbMATH Keywords: Bayesian decision framework
zbMATH Keywords: generalized additive models
zbMATH Keywords: cost-sensitive classification
zbMATH Keywords: recall guarantees
describes a project that uses: ElemStatLearn
describes a project that uses: BayesDA
describes a project that uses: PhysioToolkit
MaRDI profile type: Publication
OpenAlex ID: W3156048365
cites work: Q4420195
cites work: Sequential approaches for learning datum-wise sparse representations
cites work: Greedy function approximation: A gradient boosting machine.
cites work: Bayesian data analysis.
cites work: Learning cost-sensitive active classifiers
cites work: Q5251797
cites work: Classification with costly features as a sequential decision-making problem
cites work: Cost-sensitive feature acquisition and classification
cites work: High-dimensional covariance matrix estimation with missing observations
cites work: A review of Bayesian variable selection methods: what, how and which
cites work: Q3394879
cites work: Q4843187
cites work: Q4864293
DOI: 10.1007/S10994-021-05958-Z
Recommended article: Cost-sensitive feature acquisition and classification
Recommended article: Learning cost-sensitive active classifiers
Recommended article: Cost-sensitive active learning through statistical methods
Recommended article: Q5381119
Recommended article: Adaptive k-class estimation in high-dimensional linear models
Recommended article: Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression
description: scientific article; zbMATH DE number 7432830