a simple implementation in python of the method proposed by Zhi-Hua Zhou and Ji
Feng in their paper "Deep Forest: Towards An Alternative to Deep Neural Networks".
You can check their article here
The implementation is based on the great work of the Scikit-learn library. The API is built upon the scikit way of doing data science, by defining object with fit and predict methods. Some example will be provided soon! In the meantime, you may start by checking up the notebooks.
The recommended way to proceed for the installation is through conda environments. Using conda you need to type :
conda create -n deepforest python=3
source activate deepforest
conda install --file requirements.txt
python setup.py installThe library is currently tested on python 2.7, 3.4, 3.5 and 3.6.
If you wish to run the tests yourself, you may clone this repo and run
cd DeepForest
conda create -q -n deepforest_test python=3
source activate deepforest_test
conda install --file requirements.txt --file test-requirements.txt -q
python setup.py install
python setup.py test