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.
| Feature | Description | Medium | Gumroad/Podcast |
|---|---|---|---|
| A step-by-step guide for clustering images | Learn the basics of causal modelling. | link | --- |
| Creation of Hash image signatures | Detection of (Near) Identical Images Using Image Hash Functions. | link | --- |
| From Data to Clusters | The step to go from raw data to reliable clusters. | link | --- |
| From Clusters To Insights. | The step from clusters to valuable insights. | link | --- |
Full documentation is available at erdogant.github.io/clusteval, including examples and API references.
It is advisable to use a virtual environment:
conda create -n env_clusteval python=3.12
conda activate env_clustevalInstall via PyPI:
pip install clustevalTo upgrade to the latest version:
pip install --upgrade clustevalImport the library:
from clusteval import clustevalA structured overview is available in the documentation.
Silhouette Score |
Optimal Clusters |
Dendrogram |
Davies-Bouldin Index |
Derivative Method |
DBSCAN |
HDBSCAN A |
HDBSCAN B |
Please cite clusteval in your publications if it has been helpful in your research. Citation information is available at the top right of the GitHub page.
- Use ARI when clustering contains large equal-sized clusters
- Use AMI for unbalanced clusters with small components
- Adjusted Rand Score — scikit-learn
- Adjusted for Chance Measures — scikit-learn
- imagededup GitHub repo
- Clustering images by visual similarity
- Facebook DeepCluster
- PCA on Hyperspectral Data
- Face Recognition with PCA
Thank the contributors!
- Erdogan Taskesen, github: erdogant
- Contributions are welcome.
- Yes! This library is entirely free but it runs on coffee! :) Feel free to support with a Coffee.
