Estimate the number of clusters in your data set.
Project description
The Entropy Method is an algorithm to estimate the number of clusters in a data set.
The method relies on the stability principle. Subsamples of your data set are repeatedly clustered into different numbers of clusters; the algorithm then assesses which number of clusters provides the most stable clustering.
For more details, see the pre-print (link to be provided)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
entropymethod-0.3.3.tar.gz
(4.4 kB
view hashes)
Built Distribution
Close
Hashes for entropymethod-0.3.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f98d6bec7168a63611104809a5a26a9c969ed0c2897990d8ee2bec90e4ce3f2a |
|
MD5 | 8b7eb4ab18972ecb7e431a475a324dc4 |
|
BLAKE2b-256 | f00fc54c8d1db55dadf648938c3cac166ed97cc82211affb61403479cf78d57d |