Machine learning by construction of a decision function

Details Machine learning by construction of a decision function Machine learning by construction of a decision function

2005-04-26

2005-04-26

Rones, Charles (Department: 2164)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000, C707S793000, C707S793000, C707S793000, C345S428000, C345S440000, C345S581000, C370S401000, C370S392000

Reexamination Certificate

active

06886008

ABSTRACT:
Data processing apparatus is provided for evaluating answers to respective query items considered to be represented by respective points within a region of feature space, and the apparatus comprises an input (10) which receives such a query item. The region is subdivided into subregions according to at least first and second subdivisions. A subregion identifying portion (20) identifies, for each such subdivision of the region, which subregion of the subdivision contains the point representing the received query item. A partial answer retrieval portion (30) has access when the apparatus is in use to a store (40) of precalculated partial answers for at least some the subregions of the subdivisions, and retrieves from the store the partial answers for the or each identified subregion that is present in the store. An answer calculation portion (50) calculates an answer to the received query item based on the retrieved partial answers, and an output (60) outputs the calculated answer.

REFERENCES:
Haykin, Neural Networks, Prentice-Hall International Inc., 1999, pp. 1-3.
Duda, et al., Pattern Classification, Wiley-Interscience Publication, 2001, Second Edition, pp. 372-375.
Vapnik, Statistical Learning Theory, John Wiley & Sons, Inc., 1998, pp. 420-423.
Tikhonov, et al., Solutions of III-Posed Problems, V.H. Winston & Sons, 1977.
Evgeniou, et al., A Unified Framework for Regularization Networks and Support Vector Machines, C.B.C.L. Paper No. 171, Mar. 23, 1999, pp. 1-41.
Garcke, et al., Data Mining with Sparse Grids, Institut für Angewandte Mathematik, pp. 1-27, no date.

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