https://github.com/giannisnik/message_passing_graph_kernels
https://github.com/giannisnik/message_passing_graph_kernels
graph-classification graph-kernels
Last synced: 11 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/giannisnik/message_passing_graph_kernels
- Owner: giannisnik
- Created: 2018-08-06T09:33:45.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2020-04-11T10:16:56.000Z (almost 6 years ago)
- Last Synced: 2024-10-30T15:50:44.464Z (over 1 year ago)
- Topics: graph-classification, graph-kernels
- Language: Python
- Size: 544 KB
- Stars: 15
- Watchers: 4
- Forks: 9
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-graph-classification - [Python Reference
README
# Message Passing Graph Kernels
Code for the paper [Message Passing Graph Kernels](https://arxiv.org/pdf/1808.02510.pdf).
### Requirements
Code is written in Python 3.6 and requires:
* NetworkX 1.11
* scikit-learn 0.18
### Datasets
Download the datasets from: https://ls11-www.cs.tu-dortmund.de/staff/morris/graphkerneldatasets.
Extract the datasets into the `datasets` folder.
### Run the model
Use the following command to create the kernel matrix:
```
$ python MPGK_AA.py dataset n_iterations use_node_labels use_node_attributes
```
### Example
```
$ python MPGK_AA.py MUTAG 3 1 0
```
### Cite
Please cite our paper if you use this code:
```
@article{nikolentzos2018message,
title={Message Passing Graph Kernels},
author={Nikolentzos, Giannis and Vazirgiannis, Michalis},
journal={arXiv preprint arXiv:1808.02510},
year={2018}
}
```