Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
2005-06-14
2005-06-14
Ali, Mohammad (Department: 2167)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000
Reexamination Certificate
active
06907436
ABSTRACT:
A method for classifying data involves receiving a set of training data from a physical process such as a computer network (20). The training data has attribute data and target data. The target data has a class label associated with the attribute data. Dummy clusters are derived from centroid coordinates of the training data associated with the class label (22). Distance measures are determined between the training data and a plurality of clusters which include the dummy clusters (24). Real clusters are created in the plurality of clusters if the training data is closest to a dummy cluster or a cluster having a class label different than the class label associated with the training data (26). A closest match between data to be classified and the plurality of clusters is identified (28) and the data is classified as the class label of the closest match from the plurality of clusters (30).
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S. Garavaglia, “A heuristic self-organizing map trained using the tanimoto coefficient”, May 4-9, 1998, PP 289-295.
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Li Xiangyang
Ye Nong
Ali Mohammad
Arizona Board of Regents, acting for and on behalf of Arizona St
Atkins Robert D.
Quarles & Brady Streich & Lang LLP
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