Download Networked Digital Technologies, Part I: Second International by Filip Zavoral, Jakub Yaghob, Pit Pichappan, Eyas El-Qawasmeh PDF

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By Filip Zavoral, Jakub Yaghob, Pit Pichappan, Eyas El-Qawasmeh

This ebook constitutes the court cases of the second one foreign convention on Networked electronic applied sciences, held in Prague, Czech Republic, in July 2010.

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Networked Digital Technologies, Part I: Second International Conference, NDT 2010, Prague, Czech Republic (Communications in Computer and Information Science)

This ebook constitutes the complaints of the second one foreign convention on Networked electronic applied sciences, held in Prague, Czech Republic, in July 2010.

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Additional info for Networked Digital Technologies, Part I: Second International Conference, NDT 2010, Prague, Czech Republic (Communications in Computer and Information Science)

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Principal Component Analysis (PCA) is the main linear technique for dimension reduction. This method performs a linear mapping of given data to a lower dimensional space in such a way, that the variance of the data is maximized in the low-dimensional representation. We refer to [9, 12] for more details. In practice, correlation matrix of the data is constructed and eigenvectors of this matrix are computed. The eigenvectors corresponding to the set of largest eigenvalues (the principal components) can now be used to reconstruct a large fraction of the variance of the original data.

A survey of dimension reduction techniques. Technical report, Lawrence Livermore National Laboratory (2002) 10. : Data access optimizations for highly threaded multi-core cpus with multiple memory controllers. In: IPDPS, pp. 1–7. IEEE, Los Alamitos (2008) 11. : Learning sparse representations by non-negative matrix factorization and sequential cone programming. J. Mach. Learn. Res. 7, 1385–1407 (2006) 12. : Large-scale principal component analysis on livejournal friends network. In: Proceedings of SNAKDD 2008 (2008) 13.

Imůnek and T. Tammisto explains also the main challenges faced. There are presented the first experiences with distributed solving of data-mining tasks also in the fourth section. The last section of this paper proposes directions for further development. 2 LISp-Miner System The LISp-Miner system (developed since 1996 at University of Economics, Prague) is an academic system used mainly for data-mining research and teaching. g. [2]). cz. The system is based on many decades of related research of the GUHA method.

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