Análise de componentes principais (Portuguese Wikipedia)

Analysis of information sources in references of the Wikipedia article "Análise de componentes principais" in Portuguese language version.

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2ulb.ac.be

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2web.archive.org

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2nag.co.uk

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2doi.org

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2springer.com

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1smmu.edu.cn

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1salk.edu

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1otago.ac.nz

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1arxiv.org

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1ihes.fr

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1narod.ru

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arxiv.org

A. N. Gorban, A. Y. Zinovyev, Principal Graphs and Manifolds, In: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods and Techniques, Olivas E.S. et al Eds. Information Science Reference, IGI Global: Hershey, PA, USA, 2009. 28-59.

books.google.com

Fukunaga, Keinosuke (1990). Introduction to Statistical Pattern Recognition. [S.l.]: Elsevier. ISBN 0122698517

doi.org

dx.doi.org

Geladi, Paul; Kowalski, Bruce (1986). «Partial Least Squares Regression:A Tutorial». Analytica Chimica Acta. 185: 1–17. doi:10.1016/0003-2670(86)80028-9
Kriegel, Hans-Peter; Kröger, Peer; Schubert, Erich; Zimek, Arthur (1 de janeiro de 2008). Bertram, ed. A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms. [S.l.]: Springer Berlin Heidelberg. p. 418-435. ISBN 978-3-540-69476-2. doi:10.1007/978-3-540-69497-7_27

ihes.fr

Wang, Y., Klijn, J.G., Zhang, Y., Sieuwerts, A.M., Look, M.P., Yang, F., Talantov, D., Timmermans, M., Meijer-van Gelder, M.E., Yu, J. et al.: Gene expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365, 671-679 (2005); Data online

nag.co.uk

The Numerical Algorithms Group. «NAG Library Routine Document: nagf_mv_prin_comp (g03aaf)» (PDF). NAG Library Manual, Mark 23. Consultado em 16 de fevereiro de 2012
The Numerical Algorithms Group. «NAG Library Routine Document: nag_mv_prin_comp (g03aac)» (PDF). NAG Library Manual, Mark 9. Consultado em 16 de fevereiro de 2012. Arquivado do original (PDF) em 24 de novembro de 2011

narod.ru

pca.narod.ru

A. Gorban, B. Kegl, D. Wunsch, A. Zinovyev (Eds.), Principal Manifolds for Data Visualisation and Dimension Reduction, LNCSE 58, Springer, Berlin – Heidelberg – New York, 2007. ISBN 978-3-540-73749-0

otago.ac.nz

cs.otago.ac.nz

Informações adicionais podem ser lidas aqui

salk.edu

snl.salk.edu

Jonathon Shlens, A Tutorial on Principal Component Analysis. Arquivado em 15 de fevereiro de 2010, no Wayback Machine.

smmu.edu.cn

stat.smmu.edu.cn

Pearson, K. (1901). «On Lines and Planes of Closest Fit to Systems of Points in Space» (PDF). Philosophical Magazine. 2 (6): 559–572

springer.com

Jolliffe I.T. Principal Component Analysis, Series: Springer Series in Statistics, 2nd ed., Springer, NY, 2002, XXIX, 487 p. 28 illus. ISBN 978-0-387-95442-4

link.springer.com

Kriegel, Hans-Peter; Kröger, Peer; Schubert, Erich; Zimek, Arthur (1 de janeiro de 2008). Bertram, ed. A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms. [S.l.]: Springer Berlin Heidelberg. p. 418-435. ISBN 978-3-540-69476-2. doi:10.1007/978-3-540-69497-7_27

ulb.ac.be

A. A. Miranda, Y. A. Le Borgne, and G. Bontempi. New Routes from Minimal Approximation Error to Principal Components, Volume 27, Number 3 / June, 2008, Neural Processing Letters, Springer
A.A. Miranda, Y.-A. Le Borgne, and G. Bontempi. New Routes from Minimal Approximation Error to Principal Components, Volume 27, Number 3 / June, 2008, Neural Processing Letters, Springer

web.archive.org

Jonathon Shlens, A Tutorial on Principal Component Analysis. Arquivado em 15 de fevereiro de 2010, no Wayback Machine.
The Numerical Algorithms Group. «NAG Library Routine Document: nag_mv_prin_comp (g03aac)» (PDF). NAG Library Manual, Mark 9. Consultado em 16 de fevereiro de 2012. Arquivado do original (PDF) em 24 de novembro de 2011

wolfram.com

reference.wolfram.com

Eigenvalues function Mathematica documentation