kmodes 0.11.0-foss-2020a-Python-3.8.2
k-modes is used for clustering categorical variables. It defines clusters based on the number of matching categories between data points. (This is in contrast to the more well-known k-means algorithm, which clusters numerical data based on Euclidean distance.) The k-prototypes algorithm combines k-modes and k-means and is able to cluster mixed numerical / categorical data.Accessing kmodes 0.11.0-foss-2020a-Python-3.8.2
To load the module for kmodes 0.11.0-foss-2020a-Python-3.8.2 please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):
📋
module load kmodes/0.11.0-foss-2020a-Python-3.8.2
BEAR Apps Version
Architectures
EL8-cascadelake — EL8-icelake — EL8-sapphirerapids
The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
Extensions
- kmodes 0.11.0
More Information
For more information visit the kmodes website.
Dependencies
This version of kmodes has a direct dependency on: foss/2020a Python/3.8.2-GCCcore-9.3.0 scikit-learn/0.23.2-foss-2020a-Python-3.8.2 SciPy-bundle/2020.03-foss-2020a-Python-3.8.2
Last modified on 24th March 2021