mobForest (1.3.0)

0 users

Model Based Random Forest Analysis.

http://cran.r-project.org/web/packages/mobForest

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.

Maintainer: Kasey Jones
Author(s): 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]

License: GPL (>= 2)

Uses: modeltools, party, sandwich, strucchange, zoo, lattice, mlbench, testthat

Released about 1 year ago.


1 previous version

Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of mobForest yet. Want to be the first? Write one now.


Related packages:(20 best matches, based on common tags.)


Search for mobForest on google, google scholar, r-help, r-devel.

Visit mobForest on R Graphical Manual.