This package implements genRBF (see Generalized RBF kernel for incomplete data). The code is written in Python and Cython.
- numpy (1.12.1 or higher),
- cython (0.25.2 or higher),
- gcc, g++ (5.4.0 or higher).
To estimate a Gaussian density from incomplete data used in genRBF, we applied R package norm.
Go to directory genRBF-missing/genRBF_source/ and run the following instruction in terminal:
./build.sh
or
python setup.py build_ext --inplace
The file 'main_demo.py' applies genRBF to SVM classifier. To run this demo, type the following command in terminal:
./main_demo.py ./data/
A directory genRBF-missing/data/ contains exemplary data with missing attributes: train data, test data and their labels. Files mu.txt, cov.txt contain covariance matrix and mean estimated over train data and were created with use of norm.R:
./norm.R ./data/train_data.txt ./data/