mobForest: Model based Random Forest analysis
This package 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 mobForestAnalysis() takes
all input parameters to construct trees, compute out-of-bag
errors, predictions, and overall accuracy of forest. The
algorithm performs parallel computation using clusterApply()
function within 'parallel' package.
| Version: |
1.2 |
| Depends: |
parallel, party, lattice |
| Imports: |
methods, modeltools |
| Suggests: |
mlbench |
| Published: |
2013-01-29 |
| Author: |
Nikhil Garge, Barry Eggleston and Georgiy Bobashev |
| Maintainer: |
Nikhil Garge <ngarge at rti.org> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
mobForest results |
Downloads: