[R-pkgs] randomSurvivalForest 2.0.0 now available

K. B. Udaya ubk at kogalur-shear.com
Sun Feb 11 17:40:02 CET 2007

Dear useRs:

Release 2.0.0 of the randomSurvivalForest package is now available.


Release 2.0.0 represents a major upgrade in the functionality and stability
of the original 1.0.0 release.  Key changes are as follows:

o Two new splitting rules, 'logrankscore' and 'logrankapprox', added.

o Expanded output from 'rsf()'.  Now out-of-bag objects 'oob.ensemble' and
  'oob.mortality' are included in addition to the full ensemble objects
  'ensemble' and 'mortality'.

o Importance values for predictors can now be calculated (set
'importace = TRUE'
  in the initial 'rsf()' call).  Extended 'plot.error()' to print, as
well as plot,
  such values.

o Prediction on test data can now be implemented using 'rsf.predict()' (set
  'forest = TRUE' in the initial 'rsf()' call).

o Included option 'predictorWt' used for weighted sampling of predictors when
  growing a tree.

o Formula no longer restricted to main effects.  Formula for 'rsf' interpreted
  as in typical R applications.  However, users should be aware that including
  interactions or higher order terms in a formula may not be an optimal way to
  grow a forest.

o Three types of objects are generated in an RSF analysis: '(rsf, grow)',
  '(rsf, predict)' and '(rsf, forest)'.  Wrappers handle each type of object
  in different ways.

o Improved error checking in all wrappers.

o Extended 'plot.variable()' wrapper to generate partial plots for predictors.

o Improved control over trace output.  See the 'do.trace' option in 'rsf()'.

o Implements the Predictive Model Markup Language specification for an
  '(rsf, forest)' forest object.  PMML is an XML based language which
  provides a way for applications to define statistical and data mining
  models and to share models between PMML compliant applications.  More
  information about PMML and the Data Mining Group can be found at
  http://www.dmg.org.  Our implementation gives the user the ability to
  save the geometry of a forest as a PMML XML document for export or
  later retrieval.


ubk2101 at columbia.edu

Udaya B. Kogalur, Ph.D.
Kogalur Shear Corporation
5425 Nestleway Drive, Suite L1
Clemmons, NC 27012

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