Partially Supervised Learning Using an EM‐Boosting Algorithm-Reference-Cited by-同舟云学术

Partially Supervised Learning Using an EM‐Boosting Algorithm

Published:2004-03 Issue:1 Volume:60 Page:199-206
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Yasui Yutaka¹,Pepe Margaret¹²,Hsu Li¹,Adam Bao‐Ling³,Feng Ziding¹

Affiliation:

1. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109‐1024, U.S.A.

2. Department of Biostatistics, University of Washington, Seattle, Washington 98195‐7232, U.S.A.

3. Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, Georgia 30912, U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.0006-341X.2004.00156.x

Reference26 articles.

1. Serum protein fingerprinting coupled with a pattern‐matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men;Adam B. L.;Cancer Research,2002

2. Use of the positive predictive value to correct for disease misclassification in epidemiologic studies;Brenner H.;American Journal of Epidemiology,1993

3. A review of methods for misclassified categorical data in epidemiology

4. Nonparametric regression estimates using misclassified binary responses

5. BIAS DUE TO MISCLASSIFICATION IN THE ESTIMATION OF RELATIVE RISK

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Context-Aware Learning for Generative Models;IEEE Transactions on Neural Networks and Learning Systems;2021-08

2. On Estimation of the Hazard Function From Population-Based Case–Control Studies;Journal of the American Statistical Association;2018-04-03

3. Weakly supervised clustering: Learning fine-grained signals from coarse labels;The Annals of Applied Statistics;2015-06-01

4. Learning kernel logistic regression in the presence of class label noise;Pattern Recognition;2014-11

5. Classification of mislabelled microarrays using robust sparse logistic regression;Bioinformatics;2013-02-15