This script reproduces the experiment presented in the paper for 2 datasets.
Before launching the script, ensure to ahve the following dependencies installed:
numpy
scikit-learn
pandas
POT
(github)python-igraph
In its simplest instance, you can run the example code as follows:
python3 main.py --dataset MUTAG # or ENZYMES
Additionally, you can play with the following options (run python3 main.py -h
to display them):
usage: main.py [-h] [-d {MUTAG,ENZYMES}] [--crossvalidation] [--gridsearch]
[--sinkhorn] [--h H]
optional arguments:
-h, --help show this help message and exit
-d {MUTAG,ENZYMES}, --dataset {MUTAG,ENZYMES}
Provide the dataset name (MUTAG or Enzymes)
--crossvalidation Enables a 10-fold crossvalidation
--gridsearch Enable grid search
--sinkhorn Use sinkhorn approximation
--h H (Max) number of WL iterations
# For example:
python main.py -d ENZYMES --gridsearch --crossvalidation --h 7