Functions to implements random forest method for model based recursive partitioning. The mob() function, developed by Zeileis et al. (2008), within 'party' package, is modified to construct model-based decision trees based on random forests methodology. The main input function mobforest.analysis() takes all input parameters to construct trees, compute out-of-bag errors, predictions, and overall accuracy of forest. The algorithm performs parallel computation using cluster functions within 'parallel' package.
|Author||Nikhil Garge [aut], Barry Eggleston [aut], Georgiy Bobashev [aut], Benjamin Carper [cre], Kasey Jones [ctb, cre], Torsten Hothorn [ctb], Kurt Hornik [ctb], Carolin Strobl [ctb], Achim Zeileis [ctb]|
|Maintainer||Kasey Jones <email@example.com>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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