imbalanced-learn 0.4.3-fosscuda-2018b-Python-3.6.6

Deprecated: Use of this version of imbalanced-learn is deprecated. More information on our Applications Support and Retention Policy.

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 0.4.3-fosscuda-2018b-Python-3.6.6

To load the module for imbalanced-learn 0.4.3-fosscuda-2018b-Python-3.6.6 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):

module load imbalanced-learn/0.4.3-fosscuda-2018b-Python-3.6.6

BEAR Apps Version

2018b

Architectures

EL8-haswell (GPUs: NVIDIA P100)

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.

More Information

For more information visit the imbalanced-learn website.

Dependencies

This version of imbalanced-learn has a direct dependency on: fosscuda/2018b Python/3.6.6-fosscuda-2018b scikit-learn/0.20.0-fosscuda-2018b-Python-3.6.6

Last modified on 12th August 2019