𝔖 Bobbio Scriptorium
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Multivariate data analysis and modeling through classification and regression trees

✍ Scribed by Roberta Siciliano; Francesco Mola

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
144 KB
Volume
32
Category
Article
ISSN
0167-9473

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✦ Synopsis

This paper provides a multivariate approach to binary segmentation in order to deal with more response variables. Splitting criteria are proposed to grow decision trees with multivariate classiΓΏcation/ prediction. These are derived as extensions of criteria used in two-stage binary segmentation. The proposed methodology can be fruitfully performed not only to deΓΏne decision rules for new cases but also to explore dependency in multivariate data. The feasibility of the method and the interpretation of the ΓΏnal decision trees are discussed in a practical example using a survey of the Bank of Italy.

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