Output details
11 - Computer Science and Informatics
University of Essex
Article title
Estimating error rates in the classification of paired organs
Type
D - Journal article
DOI
Title of journal
Statistics in Medicine
Article number
-
Volume number
27
Issue number
22
First page of article
4515
ISSN of journal
02776715
Year of publication
2008
URL
-
Number of additional authors
1
Additional information
<24> The new paired cross-validation approach allows unbiased and efficient estimation of misclassification error rates in the classification of data from paired observations. The paper is an outcome of the project C1 ‘Biometric planning and modelling’ (SFB 539; funded 1997-2009) of the Deutsche Forschungsgemeinschaft (DFG) and resulted in the R package package sperroest, with more than 1100 downloads at cran-logs.rstudio in the last year. These methods were applied as part of the SFB in various fields: precision agriculture, tissue spectroscopy, nerve detection, remote sensing and clinical research.
Interdisciplinary
-
Cross-referral requested
-
Research group
A - Artificial Intelligence
Citation count
12
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
