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, BEARCloud VMs, and CaStLeS VMs):

module load kmodes/0.11.0-foss-2020a-Python-3.8.2

BEAR Apps Version

2020a

Architectures

EL8-cascadelake — EL8-haswell

The listed architectures consist of two part: OS-CPU.

  • BlueBEAR: The OS used on BlueBEAR 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.
  • BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.

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