Regularized Greedy Forest (RGF) in C++
Regularized greedy forest (RGF) 
is a tree ensemble learning method. With the code provided here, you
can do the
RGF training for regression tasks and binary classification tasks.
trained models to new data.
the RGF code archive below and extract the contents.
the executable following the instructions in README included in the code archive.
with sample data by going through the examples in the user guide .
- RGF code archive (binary was built on June 23, 2014).
Data archive used in the
experiments (excluding the competition data) in the report .
The data files in this archive were derived from parts of the data
obtained from the UCI
repository and CMU StatLib. See README
for more information on the original data sources.
Johnson and Tong Zhang. Learning nonlinear functions using regularized greedy forest,
IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(5):942-954, May 2014.
 Regularized Greedy Forest in C++
User Guide (included in the code archive)
written by Rie Johnson. Since Rie
wants to enjoy a
carefree life, the distribution of the software is
Tong Zhang. Please contact Tong Zhang for any questions about