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Prediction by collective likelihood from emerging patterns

  • US 20060074824A1
  • Filed: 08/22/2002
  • Published: 04/06/2006
  • Est. Priority Date: 08/22/2002
  • Status: Abandoned Application
First Claim
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1. A method of determining whether a test sample, having test data T, is categorized in one of a number n of classes wherein n is 2 or more, comprising:

  • extracting a plurality of emerging patterns from a training data set D that has at least one instance of each of said n classes of data;

    creating n lists, wherein;

    an ith list of said n lists contains a frequency of occurrence, ƒ

    i(m), of each emerging pattern EPi(m) from said plurality of emerging patterns that has a non-zero occurrence in an ith class of data;

    using a fixed number, k, of emerging patterns, wherein k is substantially less than a total number of emerging patterns in the plurality of emerging patterns, calculating n scores;

    wherein;

    an ith score of said n scores is derived from the frequencies of k emerging patterns in said ith list that also occur in said test data; and

    deducing which of said n classes of data the test data is categorized in, by selecting the highest of said n scores.

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