Adaptive covariate acquisition for minimizing total cost of classification

DOI10.1007/s10994-021-05958-zOpenAlexW3156048365MaRDI QIDQ2051306

Daniel Andrade, Yuzuru Okajima

Publication date: 24 November 2021

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2002.09162

zbMATH Keywords

generalized additive modelscost-sensitive classificationBayesian decision frameworkrecall guarantees

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Optimal selection of sample-size dependent common subsets of covariates for multi-task regression prediction

Uses Software

• BayesDA
• ElemStatLearn
• PhysioToolkit

Cites Work

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• Greedy function approximation: A gradient boosting machine.
• High-dimensional covariance matrix estimation with missing observations
• Cost-sensitive feature acquisition and classification
• Sequential approaches for learning datum-wise sparse representations
• Classification with costly features as a sequential decision-making problem
• Learning cost-sensitive active classifiers
• A review of Bayesian variable selection methods: what, how and which

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