Evaluation and comparison tool for different graph kernels
conda env create -f environment.yml
source activate graph_kernels
Navigate to /kernels/MLG/MLGkernel
and edit path to Eigen in Makefile.options (even if it is included globally, it could be in usr/local/include or in usr/include)
make all
Navigate to /kernels/glocalwl and use
cmake ./
make
Set -d parameter to folder names in datasets directory. In config.py you can find all currently supported kernels with their keys.
usage: evaluate.py [-h] -d DATA [DATA ...] -k KERNELS [KERNELS ...]
Starting benchmark
optional arguments:
-h, --help show this help message and exit
-d DATA [DATA ...], --data DATA [DATA ...]
Benchmark datasets
-k KERNELS [KERNELS ...], --kernels KERNELS [KERNELS ...]
Benchmark kernels