Read e-book online Advanced Techniques in Knowledge Discovery and Data Mining PDF

By Nikhil Pal

ISBN-10: 1852338679

ISBN-13: 9781852338671

Transparent and concise causes to appreciate the training paradigms. Chapters written via prime global specialists.

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Modern semiconductor manufacturing processes feature an increasing number of processing steps with an increasing complexity of the steps themselves to generate a flood of multivariate monitoring data. This exponentially increasing complexity and the associated information processing and productivity demand impose stringent requirements, which are hard to meet using state-of-the-art monitoring and analysis methods and tools. , anomaly or novelty detection, and the discovery of nonobvious multivariate dependencies of the involved parameters and the structure in the data for improved process control.

Htm, 1998. 46–50, 2000. org/, 2001. , Oracle8i - The XML enabled data management system, Proceedings of the 16th International Conference on Data Engineering, pp. 561–8, San Diego, CA, 2000. [8] Bauer C. , Data mining digs in special advertising recruitment supplement to The Washington Post, March 15, 1998. , Bornhvd, C. and Buchmann, A. 134–143, San Jose, CA, June 2000. , and Uthurusamy, R. (eds), Advances in Knowledge Discovery and Data Mining, 22 Krzysztof J. Cios and Lukasz A. Kurgan AAAI/MIT Press, 1996.

9. Principle of OCC by NOVCLASS. sufficient covering of the normal domain. In this iterative training case, a new hypersphere with center tJ+1 = xl and radius Rmax is added to the initially empty classifier iff a presented vector xl from the training set is classified as novel by the already stored J reference vectors tj according to the basic steps given earlier. The denseness of the NOVCLASS model potentially can be controlled by scaling the Rmax parameter by a scale factor η to η × Rmax in the training process.

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Advanced Techniques in Knowledge Discovery and Data Mining (Advanced Information and Knowledge Processing) by Nikhil Pal

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