Implementation of community-based graph embedding for user classification.
Project description
# reveal-graph-embedding
Implementation of community-based graph embedding for user classification.
Features
Graph-based, multi-label user classification.
Implementation of the ARCTE (Absorbing Regularized Commute Times Embedding) algorithm for graph-based feature extraction.
Both python vanilla and cython-optimized versions.
Implementation of other feature extraction methods for graphs (Laplacian Eigenmaps, Louvain, MROC).
Evaluation score and time benchmarks.
Install
### Required packages - numpy - scipy - h5py - scikit-learn - Cython - networkx - python-louvain
### Installation To install for all users on Unix/Linux:
python3.4 setup.py build sudo python3.4 setup.py install
Alternatively:
pip install reveal-graph-embedding
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Hashes for reveal-graph-embedding-0.1.4.tar.gz
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 1044df11857e0c1226fa626225d6c132ebc176e8a7040bd35f2e1377cc1a26c7 |
|
| MD5 | f3fc18c93d180aa186db594aa55aabd3 |
|
| BLAKE2b-256 | 09740d52fd5f8105499b330fafcf6155d1f2465647e6091d1a5649abb8d927e0 |
