clusteval
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.
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Blogs
Read the blog to get a structured overview how you can use clusteval.
In case you want to detect identical images, you can also use hash functionalities.
Documentation pages
On the documentation pages you can find detailed information about the working of the clusteval with many examples.
Installation
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
Import library
from clusteval import clusteval
Examples
A structured overview of all examples are now available on the documentation pages.
Citation
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
- https://scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_rand_score.html
- https://scikit-learn.org/stable/auto_examples/cluster/plot_adjusted_for_chance_measures.html#sphx-glr-auto-examples-cluster-plot-adjusted-for-chance-measures-py
- https://github.com/idealo/imagededup
- https://towardsdatascience.com/how-to-cluster-images-based-on-visual-similarity-cd6e7209fe34
- https://github.com/facebookresearch/deepcluster
- https://towardsdatascience.com/pca-on-hyperspectral-data-99c9c5178385
- https://machinelearningmastery.com/face-recognition-using-principal-component-analysis/
Maintainer
1 maintainer
Release files for clusteval 2.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| clusteval-2.1.5.tar.gz | 25.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| clusteval-2.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 57.4 kB
Release files / clusteval-2.1.5.tar.gz
| Download URL | clusteval-2.1.5.tar.gz |
|---|---|
| Size | 25.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/4.0.1 CPython/3.10.4
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Release files / clusteval-2.1.5-py3-none-any.whl
| Download URL | clusteval-2.1.5-py3-none-any.whl |
|---|---|
| Size | 32.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.4
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