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Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of Breast Cancer
School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia .
School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia .
School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia .ORCID iD: 0000-0002-4255-5130
2011 (English)Conference paper, Published paper (Refereed)
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Text
Abstract [en]

The high dimensionality of image‐based dataset can be a drawback for classification accuracy. In this study, we propose the application of fuzzy c‐means clustering, cluster validity indices and the notation of a joint‐feature‐clustering matrix to find redundancies of image‐features. The introduced matrix indicates how frequently features are grouped in a mutual cluster. The resulting information can be used to find data‐derived feature prototypes with a common biological meaning, reduce data storage as well as computation times and improve the classification accuracy

Place, publisher, year, edition, pages
2011. Vol. 1371, 65-72 p.
Keyword [en]
High-content screening, fuzzy c-means clustering, cluster validity, joint-feature-clustering.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-125035DOI: 10.1063/1.3596628ISI: 000294779500007Scopus ID: 2-s2.0-79960094383Libris ID: 16169719ISBN: 9780735409316 (print)OAI: oai:DiVA.org:liu-125035DiVA: diva2:902756
Conference
2011 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL MODELS FOR LIFE SCIENCES (CMLS-11. Toyama City, (Japan), 11–13 October 2011
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2017-06-29Bibliographically approved

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Pham, Tuan D
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
  • rtf