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The application of Principal Component Analysis to materials science data Cover

The application of Principal Component Analysis to materials science data

Data Science Journal
Volume 1 (2006): Issue 1
By: Changwon Suh,  Arun Rajagopalan,  Xiang Li and  Krishna Rajan  
Open Access
|Jan 2006

Authors

Changwon Suh

info@ubiquitypress.com

Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute, Troy NY 12180-3590 USA

Arun Rajagopalan

info@ubiquitypress.com

Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute, Troy NY 12180-3590 USA

Xiang Li

info@ubiquitypress.com

Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute, Troy NY 12180-3590 USA

Krishna Rajan

rajank@rpi.edu

Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute, Troy NY 12180-3590 USA
DOI: https://doi.org/10.2481/dsj.1.19 | Journal eISSN: 1683-1470
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Language: English
Published on: Jan 5, 2006
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Combinatorial response maps,
Data mining,
High temperature superconductors,
Materials science,
Principal component analysis (PCA)

© 2006 Changwon Suh, Arun Rajagopalan, Xiang Li, Krishna Rajan, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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