Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2011-04-26
2011-04-26
Sparks, Donald (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
Reexamination Certificate
active
07933850
ABSTRACT:
One embodiment of the present invention provides a system that constructs a functional relationship approximation from a set of data points through nonparametric regression. During operation, the system receives a training data set in an n-dimensional space. Next, the system defines a set of regression primitives in the n-dimensional space, wherein a regression primitive in the set passes through N data points in the training data set, wherein N≧n. The system then logically combines the set of regression primitives to produce a convex envelope F, such that for each point p in the n-dimensional space: (1) F(p)=0, if p is on the convex envelope; (2) F(p)<0, if p is inside the convex envelope; and (3) F(p)>0, if p is outside the convex envelope. The system next obtains the functional relationship approximation by computing an argument of the minimum of F in the n-dimensional space. The system subsequently uses the functional relationship approximation to classify data.
REFERENCES:
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Kotsiantis et al. “Bagging Model Trees for Classification Problems”, LNCS, vol. 3746/2005, Springer Berlin/Heidelberg, pp. 328-337.
Bougaev et al. “R-functions Based Classification for Abnormal Software Process Detection”, CIS, 2005, Part 1, LNAI 3801, pp. 991-996.
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Shapiro, Vadim Theory of R-Functions and Applications: A Primer, Nov. 1988 (Revised Jun. 1991), http://sal-cnc.me.wisc.edu/index.php?option=com—remository&Itemid=143&func=startdown&id=47, downloaded May 12, 2009.
Bougaev Anton A.
Gross Kenny C.
Urmanov Aleksey M.
Chang Li-Wu
Oracle America Inc.
Park Vaughan & Fleming LLP
Sparks Donald
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