Closed Sandy4321 closed 1 year ago
Hello,
This function no longer exists. Please use the following function, which is applicable to bipartite graphs as well:
from sknetwork.clustering import get_modularity
Thanks.
I see, thanks bythe way what is main difference vs networkx? https://pypi.org/project/networkx/
The main difference is that graphs are stored as sparse matrices (standard scipy format), making scikit-network more scalable. In networkx, graphs are stored as specific objects, including internal node indexing. Most algorithms of scikit-network work well for graphs with (hundreds of) millions of edges.
great, but do you have new /better algorithms ?
Yes. See Paris for hierarchical clustering (sknetwork.hierarchy.Paris) or Diffusion for node classification (sknetwork.classification.DiffusionClassifier) for instance.
do you have somewhere description for bimodularity per
https://github.com/sknetwork-team/scikit-network/blob/95cec38d56b086b95616d2f1d13a9b98c6c8b534/sknetwork/clustering/tests/test_metrics.py#L39