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Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach

  • Ursula Neumann1, 2, 3,
  • Mona Riemenschneider1, 2,
  • Jan-Peter Sowa4,
  • Theodor Baars5,
  • Julia Kälsch4,
  • Ali Canbay4 and
  • Dominik Heider1, 2, 3Email author
BioData Mining20169:36

https://doi.org/10.1186/s13040-016-0114-4

Received: 23 June 2016

Accepted: 27 October 2016

Published: 18 November 2016

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Open Peer Review reports

Pre-publication versions of this article are available by contacting info@biomedcentral.com.

Original Submission
23 Jun 2016 Submitted Original manuscript
Author responded Author comments
Reviewed Reviewer Report
Resubmission - Version 2
Submitted Manuscript version 2
Reviewed Reviewer Report
Resubmission - Version 3
Submitted Manuscript version 3
Publishing
27 Oct 2016 Editorially accepted
18 Nov 2016 Article published 10.1186/s13040-016-0114-4

How does Open Peer Review work?

Open peer review is a system where authors know who the reviewers are, and the reviewers know who the authors are. If the manuscript is accepted, the named reviewer reports are published alongside the article. Pre-publication versions of the article are available by contacting info@biomedcentral.com.

You can find further information about the peer review system here.

Authors’ Affiliations

(1)
Department of Bioinformatics, Straubing, Germany
(2)
University of Applied Science, Weihenstephan-Triesdorf, Freising, Germany
(3)
Wissenschaftszentrum Weihenstephan, Technische Universität München, Freising, Germany
(4)
Department of Gastroenterology and Hepatology, University Hospital, University Duisburg-Essen, Essen, Germany
(5)
Clinic for Cardiology, West German Heart and Vascular Centre Essen, University Hospital, University Duisburg-Essen, Essen, Germany

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