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Method and apparatus for performing real time anomaly detection

  • US 8,713,190 B1
  • Filed: 09/08/2006
  • Issued: 04/29/2014
  • Est. Priority Date: 09/08/2006
  • Status: Expired due to Fees
First Claim
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1. A method for detecting an anomalous condition in a data stream, comprising:

  • calculating, by a processor, an expected base event count for an event in the data stream for a time interval, wherein the data stream represents data with cross-classified events, wherein each cross-classified event is an event having at least two categories;

    obtaining, by the processor, an actual event count for the event in the data stream for the time interval;

    applying, by the processor, a shrinkage factor to a ratio of the actual event count and the expected base event count to obtain an actual estimated event count, wherein the shrinkage factor uses an N parameter family of functions that comprises a family of gamma functions, where N is an integer not greater than two, wherein the shrinkage factor is obtained using a kalman filter gamma-poisson shrinker; and

    detecting, by the processor, the anomalous condition in accordance with the actual event count and the actual estimated event count.

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