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Data mining method and system using regression clustering

  • US 7,539,690 B2
  • Filed: 10/27/2003
  • Issued: 05/26/2009
  • Est. Priority Date: 10/27/2003
  • Status: Expired due to Fees
First Claim
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1. A method, comprising:

  • a processor which performs the following;

    selecting a set number of functions correlating variable parameters of a dataset; and

    clustering the dataset by iteratively applying a regression algorithm and a K-Harmonic Means performance function on the set number of functions to determine a pattern in said dataset;

    wherein said clustering comprises determining distances between data points of the dataset and values correlated with the set number of functions, regressing the set number of functions using data point probability and weighting factors associated with the determined distances, calculating a difference of harmonic averages for the distances determined prior to and subsequent to said regressing, and repeating said regressing, determining and calculating upon determining the difference of harmonic averages is greater than a predetermined value.

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