GraphEmbeddings
Python implementation of the DDoS (“Histogram loss”) graph node embedding algorithm, with experiment pipelines for link prediction, node classification, and clustering. Paper: https://arxiv.org/abs/1810.03032
Install / Use
/learn @premolab/GraphEmbeddingsREADME
GraphEmbeddings
This repository contains realization of DDoS (aka Histogram loss)
algorithm for generating graph embeddings.
Structure
All code is stored in folder final_src
Realization of several embedding algorithm including our algorithm
can be found in folder transformers.
Folder io_utils contains code responsible for reading
and writing graphs and embeddings.
Folder transformation contains generic code to generate an embedding
with any available algorithm.
Other folders represent sets of experiments for comparing algorithms:
link_prediction, classification and clusterization.
How to run
To make this code work you need to replace path to necessary dataset
in file final_src/settings.py with your local path.
