Split ranger binary into lib and binary.

.gitignore

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+.Rproj.user

.travis.yml

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+language: r
+warnings_are_errors: true
+sudo: required
+
+env:
+ global:
+   - CRAN: http://cran.rstudio.com
+
+before_install:
+    - cd ./ranger-r-package/ranger
+    - sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test -y
+    - sudo apt-get -qq update
+    - sudo apt-get -qq install gcc-4.8
+    - sudo apt-get -qq install g++-4.8
+    - sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.8 90
+    - sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.8 90
+
+notifications:
+  email:
+    recipients:
+        - work@wrig.de
+    on_success: change
+    on_failure: change

NEWS.md

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+##### Version 0.3.8
+* Small fixes
+
+##### Version 0.3.7
+* Fix bug with alternative interface and prediction
+
+##### Version 0.3.6
+* Add keep.inbag option to track in-bag counts
+* Add option sample.fraction for fraction of sampled observations
+
+##### Version 0.3.5
+* Add tree-wise split.select.weights
+
+##### Version 0.3.4
+* Add predict.all option in predict() to get individual predictions for each tree for classification and regression
+* Small changes in documentation
+
+##### Version 0.3.3
+* Add case-specific random forests
+
+##### Version 0.3.2
+* Add case weights (weighted bootstrapping or subsampling)
+
+##### Version 0.3.1
+* Catch error of outdated gcc not supporting C++11 completely
+
+##### Version 0.3.0
+* Allow the user to interrupt computation from R
+* Transpose classification.table and rename to confusion.matrix
+* Respect R seed for prediction
+* Memory improvements for variable importance computation
+* Fix bug: Probability prediction for single observations
+* Fix bug: Results not identical when using alternative interface
+
+##### Version 0.2.7 
+* Small fixes for Solaris compiler
+
+##### Version 0.2.6 
+* Add C-index splitting
+* Fix NA SNP handling
+
+##### Version 0.2.5 
+* Fix matrix and gwaa alternative survival interface
+* Version submitted to JSS
+
+##### Version 0.2.4 
+* Small changes in documentation
+
+##### Version 0.2.3 
+* Preallocate memory for splitting
+
+##### Version 0.2.2 
+* Remove recursive splitting
+
+##### Version 0.2.1 
+* Allow matrix as input data in R version
+
+##### Version 0.2.0 
+* Fix prediction of classification forests in R
+
+##### Version 0.1.9 
+* Speedup growing for continuous covariates
+* Add memory save option to save memory for very large datasets (but slower)
+* Remove memory mode option from R version since no performance gain
+
+##### Version 0.1.8 
+* Fix problems when using Rcpp <0.11.4
+
+##### Version 0.1.7 
+* Add option to split on unordered categorical covariates
+
+##### Version 0.1.6 
+* Optimize memory management for very large survival forests
+
+##### Version  0.1.5 
+* Set required Rcpp version to 0.11.2
+* Fix large $call objects when using BatchJobs
+* Add details and example on GenABEL usage to documentation
+* Minor changes to documentation
+
+##### Version 0.1.4 
+* Speedup for survival forests with continuous covariates
+* R version: Generate seed from R. It is no longer necessary to set the
+  seed argument in ranger calls.
+
+##### Version 0.1.3 
+* Windows support for R version (without multithreading)
+
+##### Version 0.1.2 
+* Speedup growing of regression and probability prediction forests
+* Prediction forests are now handled like regression forests: MSE used for
+	prediction error and permutation importance
+* Fixed name conflict with randomForest package for "importance"
+* Fixed a bug: prediction function is now working for probability
+	prediction forests
+* Slot "predictions" for probability forests now contains class probabilities
+* importance function is now working even if randomForest package is
+	loaded after ranger
+* Fixed a bug: Split selection weights are now working as expected
+* Small changes in documentation

README.md

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+[![Build Status](https://travis-ci.org/mnwright/ranger.svg?branch=master)](https://travis-ci.org/mnwright/ranger)
+![CRAN Downloads month](http://cranlogs.r-pkg.org/badges/ranger?color=brightgreen)
+![CRAN Downloads overall](http://cranlogs.r-pkg.org/badges/grand-total/ranger?color=brightgreen)
+## ranger: A Fast Implementation of Random Forests
+Marvin N. Wright, wright@imbs.uni-luebeck.de
+
+### Introduction
+Ranger is a fast implementation of random forest (Breiman 2001) or recursive partitioning, particularly suited for high dimensional data. Classification, regression, probability estimation and survival forests are supported. Classification and regression forests are implemented as in the original Random Forest (Breiman 2001), survival forests as in Random Survival Forests (Ishwaran et al. 2008). For probability estimation forests see Malley et al. (2012). 
+
+Ranger is written in C++, but a version for R is avaiable, too. We recommend to use the R version. It is easy to install and use and the results are readily available for further analysis. The R version is as fast as the pure C++ version.
+
+### Installation
+To install the Ranger R package from CRAN, just run
+
+```R
+install.packages("ranger”)
+```
+
+R version >= 3.1 is required. Note that, for now, no multithreading is supported in the R version on Windows platforms (the compiler in RTools is too old).
+
+To install the C++ version of Ranger in Linux or Mac OS X you will need a compiler supporting C++11 (i.e. gcc >= 4.7 or Clang >= 3.0) and Cmake. To build start a terminal from the Ranger main directory and run the following commands
+
+```bash
+cd source
+mkdir build
+cd build
+cmake ..
+make
+```
+
+After compilation there should be an executable called "ranger" in the build directory. 
+
+To run the C++ version in Microsoft Windows please cross compile or ask for a binary.
+
+### Usage
+For usage of the R version see ?ranger in R. Most importantly, see the Examples section. As a first example you could try 
+
+```R  
+ranger(Species ~ ., data = iris)
+```
+
+In the C++ version type 
+
+```bash
+ranger --help 
+```
+
+for a list of commands. First you need a training dataset in a file. This file should contain one header line with variable names and one line with variable values per sample. Variable names must not contain any whitespace, comma or semicolon. Values can be seperated by whitespace, comma or semicolon but can not be mixed in one file. A typical call of Ranger would be for example
+
+```bash
+ranger --verbose --file data.dat --depvarname Species --treetype 1 --ntree 1000 --nthreads 4
+```
+
+If you find any bugs, or if you experience any crashes, please report to us. If you have any questions just ask, we won't bite. 
+
+### References
+* Breiman, L. (2001). Random forests. Machine learning, 45(1), 5-32.
+* Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. (2008). Random survival forests. The Annals of Applied Statistics, 841-860.
+* Malley, J. D., Kruppa, J., Dasgupta, A., Malley, K. G., & Ziegler, A. (2012). Probability machines: consistent probability estimation using nonparametric learning machines. Methods Inf Med, 51(1), 74.