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Validating Classification Trees

✍ Scribed by K.-D. Wernecke; K. Possinger; G. Kalb; J. Stein

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
168 KB
Volume
40
Category
Article
ISSN
0323-3847

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✦ Synopsis

Nonparametric statistical classification methods that work without specific requirements to the distribution of the underlying data play an important role especially in medical applications. Such a method is that of ΒͺClassification and Regression TreesΒΊ (CART), already suggested by Sonquist, 1970 and improved later on by Of essential importance for the medical practice is the assessment of the validity of the tree obtained. In this paper resampling-methods are used to this purpose. With the construction of a classification tree resulting from the validation process we not only get a valuation of the stability of the tree construction but also a tree to be applied in clinical practice.

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We propose a probability distribution for an equivalence class of classification trees (that is, those that ignore the value of the cutpoints but retain tree structure). This distribution is parameterized by a central tree structure representing the true model, and a precision or concentration coeff