Advanced Techniques in Knowledge Discovery and Data Mining by Nikhil Pal

By Nikhil Pal

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Novel Applications in Data Mining, IEEE Press, in print 2004. D. dissertation, University of Colorado at Boulder, Department of Computer Science, 2003. 54–66, 1997. htm, 2001. htm, July 2000. htm, 2001. [53] Pazzani, M. , Knowledge discovery from data? 10–3, March/April 2000. , Knowledge discovery in real databases: A report on the IJCAI-89 Workshop, AI Magazine, 11:5, pp. 68–70, Jan. 1991. , (eds), Knowledge Discovery in Databases, AAAI/MIT Press, 1991. [56] PMML, 2nd Annual Workshop on the Predictive Model Markup Language, San Francisco, CA, August 2001.

1. Illustration of a process window. 2. Analysis of Semiconductor Manufacturing Data Process specification limit Process deviation 6 sigma Off-centered process Process specification limit Process deviation 6 sigma Correlation in process 29 Process specification limit Process deviation 6 sigma Multimodality in process Fig. 2. Illustration of process window problems. ical statistical analysis approach employed for the analysis and evaluation of process-related data. Individual parameters are checked for model consistency with regard to univariate, typically Gaussian assumptions.

A probabilistic presorting of sample data for RCE (ProRCE) based on local probability estimation and sorting of the training presentation order proportional to the probability has 2. 20]. However, for the regarded application, the focus will be on the extension of RCE to BC and OCC. Extension of RCE for OCC. , production errors or system malfunctions, as deviations from the normal state. An instance of such a system has been introduced in prior work for image processing. 31] stores a number of multidimensional pixel images and generates for each pixel an internal representation of hyperspheres with uniform radii, which is quite similar to an RCE classifier with BC.

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