imbalanced-learn 0.12.3-gfbf-2023a

imbalanced-learn is a Python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance.

Accessing imbalanced-learn 0.12.3-gfbf-2023a

To load the module for imbalanced-learn 0.12.3-gfbf-2023a please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2023a
module load imbalanced-learn/0.12.3-gfbf-2023a

BEAR Apps Version

2023a

Architectures

EL8-emeraldrapids — EL8-icelake — EL8-sapphirerapids

The listed architectures consist of two parts: 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

• imbalanced-learn-0.12.3

More Information

For more information visit the imbalanced-learn website.

Dependencies

This version of imbalanced-learn has a direct dependency on: gfbf/2023a Python/3.11.3-GCCcore-12.3.0 scikit-learn/1.3.1-gfbf-2023a

Required By

This version of imbalanced-learn is a direct dependent of: HiCExplorer/3.7.2-foss-2023a

Last modified on 12th August 2026