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A Laboratory for Recursive Partytioning
Torsten Hothorn [aut, cre], Kurt Hornik [aut], Carolin Strobl [aut], Achim Zeileis [aut]
A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available.
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party 1.0-9 1 year 8 weeks ago
party 1.0-8 1 year 16 weeks ago
party 1.0-7 1 year 21 weeks ago
party 1.0-6 1 year 42 weeks ago
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party 1.0-4 1 year 45 weeks ago
party 1.0-3 2 years 5 weeks ago
party 1.0-2 2 years 26 weeks ago
party 1.0-10 1 year 1 week ago
party 1.0-1 2 years 31 weeks ago
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