clusteval is a python package that is developed to evaluate detected clusters and return the cluster labels that have most optimal clustering tendency, Number of clusters and clustering quality. Multiple evaluation strategies are implemented for the evaluation; silhouette, dbindex, and derivative, and four clustering methods can be used: agglomerative, kmeans, dbscan and hdbscan.
Read the blog to get a structured overview how you can use
In case you want to detect identical images, you can also use hash functionalities.
On the documentation pages you can find detailed information about the working of the
clusteval with many examples.
It is advisable to create a new environment (e.g. with Conda).
conda create -n env_clusteval python=3.8 conda activate clusteval
Install from PyPI
pip install clusteval
from clusteval import clusteval
A structured overview of all examples are now available on the documentation pages.
Please cite clusteval in your publications if this is useful for your research (see right top for citation).
Other interesting techniques/blogs
- Use ARI when the ground truth clustering has large equal sized clusters
- Usa AMI when the ground truth clustering is unbalanced and there exist small clusters