Tackling ordinal regression problem for heterogeneous data: sparse and deep multi-task learning approaches

DOI10.1007/s10618-021-00746-8zbMath1478.62190arXiv1907.12508OpenAlexW3136286566MaRDI QIDQ2036753

Dongxiao Zhu, Lu Wang

Publication date: 30 June 2021

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.12508

zbMATH Keywords

diagnosisordinal regressionheterogeneous datamulti-task learningdeep neural networkmulti-stage disease progressionnon-IID learning

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Artificial neural networks and deep learning (68T07) General nonlinear regression (62J02) Neural nets and related approaches to inference from stochastic processes (62M45)

Uses Software

• ORCA

Cites Work

• Support Vector Ordinal Regression
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• Differentially private nearest neighbor classification
• Conditional ordinal random fields for structured ordinal-valued label prediction
• Prediction of Functional Status for the Elderly Based on a New Ordinal Regression Model
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