Classifying Numeric Information

نویسنده

  • Michael Lebowitz
چکیده

Learning programs that try to generalize from real-world examples may have to deal with many different kinds of data. Continuous numeric data may cause problems for algorithms that search for identical aspects of examples. This problem can be .. . surmounted by categori=ing the nume-ric data. However, this process has problems of its own. In this paper we look at the need for categorizing numeric data, and several methods for doing so. \V e concentrate on the use of a heuristic, looking for gaps, that has been implemented in the UNIMEM computer system. An example is presented of this algorithm categorizing data about states of the United States.

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تاریخ انتشار 2004