Skip to content
This is the implementation of Sparse Projection Oblique Randomer Forest
C++ R Python Makefile Dockerfile Shell Other
Branch: staging
Clone or download
MrAE update max_features to accept a fraction > 1.0 (#340)
* update max_features to accept a fraction > 1.0

* put inequality in easier to read form.
Latest commit a7a3c7e Dec 3, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.github issue templates for bugs and feat. req. (#277) May 31, 2019
Python update max_features to accept a fraction > 1.0 (#340) Dec 3, 2019
R-Project Add S-RerF to R (#295) Jun 17, 2019
docker adds Python readme to pypi landing page (#267) May 16, 2019
docs add link to netlify for hosting agreement (#338) Oct 4, 2019
packedForest add avg num leaf node per tree to tree stats output. (#302) Aug 13, 2019
.gitattributes this will set maxDepth (#181) Feb 28, 2019
.gitignore
.gitmodules Basic initial push May 3, 2018
.travis.yml add link to netlify for hosting agreement (#338) Oct 4, 2019
README.md fix badge Aug 27, 2019
netlify.toml 3rd times the charm (#325) Sep 18, 2019
pytest.ini adds python binding to packedForest (#174) Feb 21, 2019
runtime.txt

README.md

SPORF/RerF

arXiv shield PyPI version CRAN Status Badge DOI dockerhub Gigantum Downloads shield

SPORF -- sparse projection oblique randomer forests (aka RerF, Randomer Forest or Random Projection Forests) -- is an algorithm developed by Tomita et al. (2016) which is similar to Random Forest-Random Combination (Forest-RC) developed by Breiman (2001).

The difference between the two algorithms is where the random linear combinations occur: Forest-RC combines features at the tree level whereas RerF combines features at the node level.

Packages

packedForest (C++)

  • Memory optimized C++ implementation of RandomForest and RerF.

Py-RerF

  • Python bindings to packedForest.

R-RerF

  • The R and C++ implemetation of RerF.
You can’t perform that action at this time.