Ilaria asked 3 years ago
Hi,
I have a dataset with 6 entities, each entity has 20 attributes. I am investigating the cluster structure considering that the 6 entities shares some attributes. The clustering method that I am using is the Louvain resolution method.
There are 3 attributes that are shared by all the entities. I expected these attributes to influence the cluster structure. But in the final cluster, these shared attributes are shown as isolated nodes. So characterized by a degree=0. Could you please explain how the degree is calculated in this case?
Thank you.
Lionel Staff answered 3 years ago
Dear Ilaria,
Not sure to understand well what you are describing. Basically, you should have nodes (keywords, entities…) and edges (links between entities often based on a proximity measure).
Degree and consequently isolated nodes are directly affected by:
- The proximity measure used to build the edges
- The filters on edges used
I hope it helps!