Author: Yuzhen Liu
Started From 2019.3.22
Light-weighted Statistic ML implementations in C++. Algorithms included are linear regression, Logistic Regression Classifier, Sofrmax Classifier, C4.5 Decision Tree, Random Forest, GBDT, FM, Naive Bayes Classifier, SVM.

Requeirs C++ algebra library armadillo, installation of armadillo is as follows:

install denpencies first (Tested for Ubuntu 16.04):

sudo apt-get install libopenblas-dev
sudo apt-get install liblapack-dev
sudo apt-get install libarpack2-dev
sudo apt-get install libsuperlu-dev

download armadillo (armadillo-9.300.2 tested) as xxx.tar, cd and build it.

cd armadillo-9.300.2
cmake .
make
sudo make install

clone and build Arma_ML directly in place

git clone https://github.com/codestorm04/Arma_ML.git
cd Arma_ML
make

or build and install

make install

examples/ are the usage demos of each modules, reference to README.md

1. Build strategies: Reference
2. decision tree pruning
3. models: knn, LDA, PCA, MDS, k-means, FFM
4. params setting
5. normalization: L1 L2
6. optimazers other than SGD
7. model saver / loader
8. oprimizers, metrics, console visualization module