For the last eight years, microarray-based class prediction has been the subject of numerous publications in medicine, bioinformatics and statistics journals. However, in many articles, the assessment of classification accuracy is carried out using suboptimal procedures and is not paid much attention. In this paper, we carefully review various statistical aspects of classifier evaluation and validation from a practical point of view. The main topics addressed are accuracy measures, error rate estimation procedures, variable selection, choice of classifiers and validation strategy.
Description
Evaluating Microarray-based Classifiers: An Overview
%0 Journal Article
%1 boulesteix:2008-eval
%A Boulesteix, A L
%A Strobl, C
%A Augustin, T
%A Daumer, M
%D 2008
%J Cancer Inform
%K classification classifiers discriminant discriminant-analysis high-dimensional high-dimensional-data microarray
%P 77--97
%T Evaluating microarray-based classifiers: an overview
%U http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2623308/
%V 6
%X For the last eight years, microarray-based class prediction has been the subject of numerous publications in medicine, bioinformatics and statistics journals. However, in many articles, the assessment of classification accuracy is carried out using suboptimal procedures and is not paid much attention. In this paper, we carefully review various statistical aspects of classifier evaluation and validation from a practical point of view. The main topics addressed are accuracy measures, error rate estimation procedures, variable selection, choice of classifiers and validation strategy.
@article{boulesteix:2008-eval,
abstract = {For the last eight years, microarray-based class prediction has been the subject of numerous publications in medicine, bioinformatics and statistics journals. However, in many articles, the assessment of classification accuracy is carried out using suboptimal procedures and is not paid much attention. In this paper, we carefully review various statistical aspects of classifier evaluation and validation from a practical point of view. The main topics addressed are accuracy measures, error rate estimation procedures, variable selection, choice of classifiers and validation strategy.},
added-at = {2011-05-30T11:30:47.000+0200},
author = {Boulesteix, A L and Strobl, C and Augustin, T and Daumer, M},
biburl = {https://www.bibsonomy.org/bibtex/2455426c0f4b0a46c4fc8cb3b259182c3/vivion},
description = {Evaluating Microarray-based Classifiers: An Overview},
interhash = {582020cf66d820183d9dc7f1fd1e97bc},
intrahash = {455426c0f4b0a46c4fc8cb3b259182c3},
journal = {Cancer Inform},
keywords = {classification classifiers discriminant discriminant-analysis high-dimensional high-dimensional-data microarray},
pages = {77--97},
pmid = {19259405},
timestamp = {2011-05-30T11:30:47.000+0200},
title = {Evaluating microarray-based classifiers: an overview},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2623308/},
volume = 6,
year = 2008
}