A condensed machine learning library written in C++/CUDA.
Data types
- Image and Genome types included
- Plugin interface for creating your own data types
Dimensionality reduction
- Principal Component Analysis
- Linear Discriminant Analysis
- Independent Component Analysis
Classification
- k-Nearest Neighbors
- Naive Bayes
Clustering
- k-means
- Gaussian mixture models
This project depends on CUDA. The CUDA Toolkit can be downloaded here.
Install all other dependencies:
sudo apt-get install libblas-dev liblapacke-dev
Append these lines to ~/.bashrc:
# CUDADIR should point to your CUDA installation
export CUDADIR="/usr/local/cuda"
export PATH="$CUDADIR/bin:$PATH"
export LD_LIBRARY_PATH="$CUDADIR/lib64:$LD_LIBRARY_PATH"
export INSTALL_PREFIX="$HOME/software"
export LD_LIBRARY_PATH="$INSTALL_PREFIX/lib:$LD_LIBRARY_PATH"
You should then be able to install mlearn:
# clone repository
git clone https://github.com/CUFCTL/mlearn.git
cd mlearn
# install library
make -j [num-jobs]
Refer to the test programs in the test folder for example uses of mlearn:
make examples
cd test
build/test-classification
build/test-clustering
build/test-data
build/test-matrix