HDBSCAN 0.8.39-gfbf-2023a

The hdbscan library is a suite of tools to use unsupervised learning to find clusters, or dense regions, of a dataset. The primary algorithm is HDBSCAN* as proposed by Campello, Moulavi, and Sander. The library provides a high performance implementation of this algorithm, along with tools for analysing the resulting clustering.

Accessing HDBSCAN 0.8.39-gfbf-2023a

To load the module for HDBSCAN 0.8.39-gfbf-2023a please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2023a
module load HDBSCAN/0.8.39-gfbf-2023a

BEAR Apps Version

2023a

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.

More Information

For more information visit the HDBSCAN website.

Dependencies

This version of HDBSCAN has a direct dependency on: gfbf/2023a Python/3.11.3-GCCcore-12.3.0 scikit-learn/1.4.2-gfbf-2023a SciPy-bundle/2023.07-gfbf-2023a

Required By

This version of HDBSCAN is a direct dependent of: modbamtools/0.4.8-gfbf-2023a

Other Versions

These versions of HDBSCAN are available on the BEAR systems (BlueBEAR and BEAR Cloud VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 8th November 2024