Awesome
THE BASIC Random Jungle (RJ) README
See "INSTALL" for help on installation
INTRODUCTION
This directory contains the source code, tests, autobuild files and autobuild tools for RJ. RJ is a generalized implementation of Random Forests(tm) (RF) by Leo Breiman and Adele Cutler. In genetics, it is an well established method for analysing genetic data (i.e. GWA data).
RJ is free software distributed under a GNU-style copyleft.
RF is a powerful machine learning method. Most interesting features:
- Variable selection:
Estimates the importance of variables - Efficiency:
It runs efficiently on large data - Missing values:
It has an effective method for estimating missing data - Classifier:
It creates classifier for further analyses - General. err.:
It generates an internal unbiased estimate of the generalization error as the building progresses - Proximities:
It computes proximities between pairs of cases that can be used in clustering, locating outliers, or (by scaling) give interesting views of the data. Can be used as the distance matrix for Multidimensional Scaling (MDS)
HISTORY
RJ was initially written by Daniel F. Schwarz of the Institute of Medical Biometry and Statistics of University of Lubeck in Germany. He started in the beginning of 2008.
GOALS
Create a machine learning tool for analysing data as an equivalent to alternative statistical methods.
DEPS
UBUNTU (packages):
- gcc
- g++
- libboost-dev
- zlib1g-dev
- libgsl0-dev
- libxml2-dev
MPI:
- mpi-default-dev
- mpi-default-bin
Linker libraries:
- xml2
- gsl
- gslcblas
- z
Make documentation:
- texinfo
- texlive
Sincerely, Daniel