Preliminary study on bolstered error estimation in high-dimensional spaces Conference Paper

abstract

• Error estimation is fundamental in GSP applications, such as the discovery of biomarkers to classify disease, or the construction of genetic regulatory networks, especially in small sample settings. Braga-Neto and Dougherty proposed a kernel-based technique of error estimation, called bolstered error estimation, which was shown empirically to work well in low-dimensional spaces (Braga-Neto and Dougherty, 2004). We present in this paper preliminary results of a simulation study on how bolstering performs in high-dimensional spaces. 2008 IEEE.

name of conference

• 2008 IEEE International Workshop on Genomic Signal Processing and Statistics

authors

• Braga Neto, Ulisses
• Dougherty, Edward

published proceedings

• 2008 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS

author list (cited authors)

• Vu, T. T., Braga-Neto, U., & Dougherty, E. R.

citation count

• 2

complete list of authors

• Vu, TT||Braga-Neto, U||Dougherty, ER

publication date

• January 2008

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics  Journal

Digital Object Identifier (DOI)

• 10.1109/gensips.2008.4555687

International Standard Book Number (ISBN) 13

• 978-1-4244-2371-2

start page

• 110

end page

• 111

URL

• http://dx.doi.org/10.1109/gensips.2008.4555687