Skip Navigation



Bioinformatics Advance Access published online on February 2, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti294
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
21/9/1979    most recent
bti294v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Fu, W. J.
Right arrow Articles by Wang, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Fu, W. J.
Right arrow Articles by Wang, S.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics © Oxford University Press 2005; all rights reserved.
Received October 20, 2004
Revised January 20, 2005
Accepted January 21, 2005

Article

Estimating misclassification error with small samples via bootstrap cross-validation

Wenjiang J. Fu 1*, Raymond J. Carroll 1, and Suojin Wang 1

1 Department of Statistics, Texas A & M University, 447 Blocker Building, College Station, TX 77843 USA

* To whom correspondence should be addressed.
Wenjiang J. Fu, E-mail: wfu{at}stat.tamu.edu


  Abstract

Motivation: Estimation of misclassification error has received increasing attention in clinical diagnosis and bioinformatics studies, especially in small sample studies with microarray data. Current error estimation methods are not satisfactory because they either have large variability (such as leave-one-out cross-validation) or large bias (such as resubstitution and leave-one-out bootstrap). While small sample size remains one of the key features of costly clinical investigations or of microarray studies that have limited resources in funding, time and tissue materials, accurate and easy-to-implement error estimation methods for small samples are desirable and will be beneficial.

Results: A bootstrap cross-validation method is studied. It achieves accurate error estimation through a simple procedure with bootstrap resampling, and only costs computer CPU time. Simulation studies and applications to microarray data demonstrate that it performs consistently better than its competitors. This method possesses several attractive properties: (1) it is implemented through a simple procedure; (2) it performs well for small samples with sample size as small as 16; and (3) it is not restricted to any particular classification rules and thus applies to many parametric or non-parametric methods.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 JDRHome page
E.L. Hendrickson, R.J. Lamont, and M. Hackett
Tools for Interpreting Large-scale Protein Profiling in Microbiology
Journal of Dental Research, November 1, 2008; 87(11): 1004 - 1015.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
M. Schumacher, H. Binder, and T. Gerds
Assessment of survival prediction models based on microarray data
Bioinformatics, July 15, 2007; 23(14): 1768 - 1774.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Pang, A. Lin, M. Holford, B. E. Enerson, B. Lu, M. P. Lawton, E. Floyd, and H. Zhao
Pathway analysis using random forests classification and regression
Bioinformatics, August 15, 2006; 22(16): 2028 - 2036.
[Abstract] [Full Text] [PDF]

Home page
 Brief BioinformHome page
P. Larranaga, B. Calvo, R. Santana, C. Bielza, J. Galdiano, I. Inza, J. A. Lozano, R. Armananzas, G. Santafe, A. Perez, et al.
Machine learning in bioinformatics
Brief Bioinform, March 1, 2006; 7(1): 86 - 112.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.