By Carmela Cappelli, Francesco Mola (auth.), Prof. Dr. Hans-Hermann Bock, Prof. Marcello Chiodi, Prof. Antonino Mineo (eds.)
This quantity incorporates a number of papers awarded in the course of the biennial assembly of the category and information research crew (CLADAG) of the Societa Italiana di Statistica which used to be orga nized by way of the Istituto di Statistica of the Universita degli Studi di Palermo and held within the Palazzo Steri in Palermo on July 5-6, 2001. For this convention, and after checking the submitted four web page abstracts, fifty four papers have been admitted for presentation. They lined a wide variety of themes from multivariate facts research, with distinctive emphasis on type and clustering, computa tional records, time sequence research, and functions in a variety of classical or contemporary domain names. A two-fold cautious reviewing technique ended in the choice of twenty-two papers that are awarded during this vol ume. they communicate both a brand new thought or technique, current a brand new set of rules, or obstacle a fascinating software. now we have clustered those papers into 5 teams as follows: 1. type tools with functions 2. Time sequence research and comparable equipment three. laptop in depth ideas and Algorithms four. class and information research in Economics five. Multivariate research in technologies. In each one part the papers are prepared in alphabetical order. The editors - of them the organizers of the CLADAG confer ence - want to show their gratitude to the authors whose enthusiastic participation made the assembly attainable and intensely successful.
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Extra info for Advances in Multivariate Data Analysis: Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Palermo, July 5–6, 2001
LEE, J . Comput er Graphics and Image Processing, 17, 24-32. C. (1999) Symbolic Approach to SAR Image Classification . In : Proceedings of the IEEE 1999 International Geosciences and Remote Sensing Symposium, Hamburg, 1318-1320. , DIDAY , E. (1996) A knowl edge acquisition system based on the Cartesian Space Model. In : Diday, E. ) : Ordinal and Symboli c Data Analysis, Springer, Heid elberg, 113-122 . it Abstract. Several proximity measures have been proposed to compare classifications derived from different clustering algorithms (Gordon (1999» .
In CART the decrease in impurity achieved when passing from t to ti. and t n is defined as: where PL and PR denote the proportion of cases in tt. and in t n . Hdt , s) ex: L1Sdt, s) = eUtL - Yt)2 pL + ('f}tR - Yt)2 pR = PLPR(YtL - YtR)2 (7) Notice that the decrease in impurity in (4) and (6) is given by the difference between total heterogeneity and within nodes heterogeneity, coinciding with the between nodes heterogeneity. Consider now the problem of growing a classification tree when the G levels of Yare ordered.
And SCHAPIRE, R . (1996) : Experiments with a New Boosting Algorithm. Machin e Learning: Proceedings of the Thirteenth International Conf erence, July 1996. Proximity Measures Between Classification Trees 37 FREUND, Y. and SCHAPIRE, R. (1999): A Short Introduction to Boosting. Journal of Japanese Society for Artificial Intelligence, 14, 771-780. GORDON , A. D . (1999) : Classification, 2nd edition. Chapman and Hall/CRC, London. HUBERT, L. and ARABIE, P. (1985): Comparing Partitions. Journal of Classification , 2, 193-218.
Advances in Multivariate Data Analysis: Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Palermo, July 5–6, 2001 by Carmela Cappelli, Francesco Mola (auth.), Prof. Dr. Hans-Hermann Bock, Prof. Marcello Chiodi, Prof. Antonino Mineo (eds.)
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