Open boersmamarcel opened 5 years ago
@AlexWorldD if you have other metric in mind, then I'm open for suggestions.
It would be nice if we can get a notebook which evaluates the results of the toy-example. Present:
Can we apply a clustering algorithm; In this case we put in, for example, 10-core processes we added realistic noise. If I apply a clustering algorithm, would I then be able to find the 10-core processes correctly?
I would like to use this to evaluate the clusters obtained in real data, when the processes are classified as one core-processes or another then I can discuss the obtained clusters with an expert.
When we have good embeddings we should yield useful clusters, in one paper (Zhang et al: Learning Node Embeddings in Interaction Graphs) I found the following paragraph describing that we can evaluate the performance of the clusters:
with our toy-set we can create ground-truth labels and evaluate the embedding technique. We can even compare this with directly applying other techniques (metapath2vec,deepwalk etc)
for the real data-sets no ground truth is known hence we must describe it in a different way.