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Data Set Editing by Ordered Projection

Jesús S. Aguilar, José C. Riquelme, Miguel Toro

We present an editing algorithm based on the projection of the examples in each dimension.The algorithm, that we have called EOP, has some interesting characteristics: important reduction of the number of examples from the database; lower computational cost in respect of other typical algorithms due to the absence of distance calculations; conservation of the decision boundaries, especially from the point of view of the application of axis-parallel classifiers; reduction of the decision tree size or the number of decision rules. The performance of EOP is showed by comparing the results provided by C4.5 before and after applying it on databases with continuous attributes. The use of EOP as preprocessing method for the later application of any axis-parallel learning algorithm convert it in a valuable tool in the field of data mining.

Keywords: Editing algorithms, Axis-Parallel classifiers, Data mining

Citation: Jesús S. Aguilar, José C. Riquelme, Miguel Toro: Data Set Editing by Ordered Projection. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.251-255.

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ECAI-2000 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Humboldt University on behalf of Gesellschaft für Informatik.