Resource title

Evaluating Model-based Trees in Practice

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Resource description

A recently suggested algorithm for recursive partitioning of statistical models (Zeileis, Hothorn and Hornik, 2005), such as models estimated by maximum likelihood or least squares, is evaluated in practice. The general algorithm is applied to linear regression, logisitic regression and survival regression and applied to economical and medical regression problems. Furthermore, its performance with respect to prediction quality and model complexity is compared in a benchmark study with a large collection of other tree-based algorithms showing that the algorithm yields interpretable trees, competitive with previously suggested approaches. (author's abstract) ; Series: Research Report Series / Department of Statistics and Mathematics

Resource author

Achim Zeileis, Torsten Hothorn, Kurt Hornik

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Resource language

en

Resource content type

application/pdf

Resource resource URL

http://epub.wu.ac.at/1484/1/document.pdf

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Adapt according to the license agreement. Always reference the original source and author.