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.
| Version: | 1.3.1 |
| Depends: | parallel (≥ 3.4.1), party (≥ 1.2-4), sandwich (≥ 2.4.0), strucchange (≥ 1.5-1), zoo (≥ 1.8-0) |
| Imports: | methods, modeltools, stats, graphics |
| Suggests: | testthat (≥ 1.0.2), mlbench (≥ 2.1), lattice |
| Published: | 2019-07-31 |
| 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 <krjones at rti.org> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | mobForest results |
| Reference manual: | mobForest.pdf |
| Package source: | mobForest_1.3.1.tar.gz |
| Windows binaries: | r-devel: mobForest_1.3.1.zip, r-release: mobForest_1.3.1.zip, r-oldrel: mobForest_1.3.1.zip |
| macOS binaries: | r-release: mobForest_1.3.1.tgz, r-oldrel: mobForest_1.3.1.tgz |
| Old sources: | mobForest archive |
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