A least squares algorithm for fitting additive trees to proximity data |
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Authors: | Geert De Soete |
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Institution: | (1) Department of Psychology, University of Ghent, Henri Dunantlaan 2, B-9000 Ghent, Belgium |
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Abstract: | A least squares algorithm for fitting additive trees to proximity data is described. The algorithm uses a penalty function to enforce the four point condition on the estimated path length distances. The algorithm is evaluated in a small Monte Carlo study. Finally, an illustrative application is presented.The author is Aspirant of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek . The author is indebted to Professor J. Hoste for providing computer facilities at the Institute of Nuclear Sciences at Ghent. |
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Keywords: | tree structures clustering proximity data |
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