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Scalable set oriented classifier

  • US 5,899,992 A
  • Filed: 02/14/1997
  • Issued: 05/04/1999
  • Est. Priority Date: 02/14/1997
  • Status: Expired due to Term
First Claim
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1. A method for classifying set-oriented data in a computer by generating a classification tree, the computer being coupled to a data storage device for storing the set-oriented data, the method comprising the steps of:

  • storing the set-oriented data as a table in a relational database in the data storage device coupled to the computer, the table being comprised of rows having attributes and node identifiers, wherein each node identifier indicates a node in the classification tree to which a row belongs;

    iteratively performing a sequence of steps in the computer until all of the rows have been classified, the sequence of steps comprising;

    determining a gini index value for each split value of each attribute for each node that can be partitioned in the classification tree;

    selecting an attribute and a split value for each node that can be partitioned based on the determined gini index value corresponding to the split value of the attribute; and

    growing the classification tree by a new level based on the selected attribute and split value for each node that can be partitioned, further comprising;

    using the node identifier associated with a row to locate a node in the classification tree;

    identifying the selected split value for that node;

    applying the split value to the row; and

    updating the node identifier according to the result of the split test.

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