Abstract
We have a class of statistical units from a population, for which the data table may contain symbolic data; that is rather than having a single value for an observed variable, an observed value for the aggregated statistical units we treat here may be multivalued. Our aim is to describe a partition of this class of statistical units by further partitioning it, where each class of the partition is described by a conjunction of characteristic properties. We use a stepwise top-down binary tree method. At each step we select the best variable and its optimal splitting to optimize simultaneously a discrimination criterion given by a prior partition and a homogeneity criterion; we also aim to insure that the descriptions obtained describe the units in the class to describe and not the rest of the population. We present a real example.
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© 2005 Springer-Verlag Berlin · Heidelberg
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Diday, E., Limam, M.M., Winsberg, S. (2005). A Tree Structured Classifier for Symbolic Class Description. In: Baier, D., Decker, R., Schmidt-Thieme, L. (eds) Data Analysis and Decision Support. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28397-8_3
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DOI: https://doi.org/10.1007/3-540-28397-8_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26007-3
Online ISBN: 978-3-540-28397-3
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