Weighted-Metapath2Vec
Weighted-Metapath2Vec is a Python package to embed heterogeneous graphs. The algorithm uses a weighted alternative to Metapath2vec to compute the embeddings. The embeddings can be used for downstream machine learning.
Installation
pip install weighted-metapath2vec
Usage
from weighted_metapath2vec import WeightedMetapath2VecModel
... # Load a networkx graph as G
metapaths = [
['Article', 'Author', 'Article'],
['Author', 'Article', 'Author']
]
model = WeightedMetapath2VecModel(G,
metapaths,
walk_length=3,
n_walks_per_node=20,
embedding_dim=128)
node_embeddings = model.fit_transform()
... # downstream task
Contributing
Use GitHub to fork and submit pull requests.
License
MIT License. See the LICENSE file.
1 maintainer
Metadata
1 maintainer
Release files for weighted-metapath2vec 0.1.4
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Total release size: 9.2 kB
Release files / weighted-metapath2vec-0.1.4.tar.gz
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