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Method for training an adaptive statistical classifier to discriminate against inproper patterns

  • US 5,768,422 A
  • Filed: 08/08/1995
  • Issued: 06/16/1998
  • Est. Priority Date: 08/08/1995
  • Status: Expired due to Term
First Claim
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1. A method for training a statistical classifier to estimate the probabilities that input patterns are associated with each of a predetermined set of classes, comprising the steps of:

  • selecting a first, positive set of training patterns each associated with a class in said set;

    selecting a second, negative set of training patterns not associated with any class in said set;

    combining said first set and said second sets into a training set;

    processing training patterns in said training set through a process comprising the following steps for each training pattern that is processed;

    computing a set of target values corresponding to each class in said set of classes, such that;

    for a training pattern from said first, positive set, the target value corresponding to its associated class is substantially equal to a first predetermined value, and the other target values of said set of target values are all substantially equal to a second predetermined value that is substantially different from said first predetermined value, and;

    for a training pattern from said second set, negative set, all of said target values are substantially equal to said second predetermined value; and

    providing said training pattern and said set of target values to a statistical classifier and training said classifier in accordance therewith.

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