Detection of Interdependences in Attribute Selection

نویسندگان

  • Javier Lorenzo-Navarro
  • Mario Hernández-Tejera
  • Juan Méndez
چکیده

A new measure for attribute selection, called GD, is proposed. The GD measure is based on Information Theory and allows to detect the interdependence between attributes. This measure is based on a quadratic form of the MM antaras distance and a matrix called Transin-formation Matrix. In order to test the quality of the proposed measure, it is compared with other two feature selection methods, namely MM antaras distance and Relief algorithms. The comparison is done over 19 datasets along with three diierent induction algorithms.

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تاریخ انتشار 1998