How many samples are needed to build a classifier: a general sequential approach-Reference-Cited by-同舟云学术

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How many samples are needed to build a classifier: a general sequential approach

Published:2004-08-05 Issue:1 Volume:21 Page:63-70
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:Bioinformatics

Author:

Fu W. J.,Dougherty E. R.,Mallick B.,Carroll R. J.

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/21/1/63/561167/bth461.pdf

Reference10 articles.

1. Selection bias in gene extraction on the basis of microarray gene-expression data

2. Parameter estimation following group sequential hypothesis testing

3. Unbiased estimation following a group sequential test

4. Molecular portraits of human breast tumours

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1. Gut-host Crosstalk: Methodological and Computational Challenges;Digestive Diseases and Sciences;2020-02-03

2. Minimum information for training a classifier;Model Assisted Statistics and Applications;2018-10-31

3. Statistical Aspects in Proteomic Biomarker Discovery;Methods in Molecular Biology;2016

4. Editor's Special Invited Paper: Sequential Estimation for Time Series Models;Sequential Analysis;2014-04-03

5. The comprehensive diagnostic study: a new solution to old problems?;Journal of Clinical Epidemiology;2014-02

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