Abstract
Rectangular decomposition [6] has proved to be useful for supervised data classification, for learning, or data organisation, and information extraction [7]. In this paper, we propose an adaptation of rectangular decomposition to non supervised data classification. Initial experiments and comparison with main other classification methods, have given us promising results. The proposed approach is based on successive optimal rectangle selection, from which we extract different classes that give a partition.
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© 1999 Springer-Verlag Berlin Heidelberg
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Sellami, H.M., Jaoua, A. (1999). Non-supervised Rectangular Classification of Binary Data. In: Imam, I., Kodratoff, Y., El-Dessouki, A., Ali, M. (eds) Multiple Approaches to Intelligent Systems. IEA/AIE 1999. Lecture Notes in Computer Science(), vol 1611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48765-4_68
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DOI: https://doi.org/10.1007/978-3-540-48765-4_68
Publisher Name: Springer, Berlin, Heidelberg
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