Abstract
In the framework of binary segmentation, we introduce alternative splitting criteria based on the predictability r index of Goodman and Kruskal. We use such splitting criteria in a two-stage predictive splitting procedure. Furthermore, we introduce as stopping rule a statistical test based on the CATANOVA statistic of Light and Margolin. We show an example on a real data set.
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© 1994 Springer-Verlag Berlin Heidelberg
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Mola, F., Siciliano, R. (1994). Alternative strategies and CATANOVA testing in two-stage binary segmentation. In: Diday, E., Lechevallier, Y., Schader, M., Bertrand, P., Burtschy, B. (eds) New Approaches in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-51175-2_37
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DOI: https://doi.org/10.1007/978-3-642-51175-2_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-58425-4
Online ISBN: 978-3-642-51175-2
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