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Scikit-Learn

Description

Scikit-Learn provides simple and efficient tools for data mining and data analysis, and is accessible to everybody. It is built on Numpy, Scipy and Matplotlib.

Access

Scikit-Learn is available on all HPRC clusters, including Grace, FASTER, ACES, and Launch. Scikit-Learn is open to all HPRC users.

Anaconda and Scikit-Learn Packages

TAMU HPRC currently supports the user of Scikit-Learn though the module system. 

module spider scikit-learn

module load scikit-learn/1.4.0

You can learn more about the module system on our SW:Modules page.

Example Scikit-Learn Script

As with any job on the system, Scikit-Learn should be used via the submission of a job file. Scripts using Scikit-Learn are written in Python, and thus Scikit-Learn scripts should not be written directly inside a job file or entered in the shell line by line. Instead, a separate file for the Python/Scikit-Learn script should be created, which can then be executed by the job file.

To create a new script file, simply open up the text editor of your choice.

Below is an example script (for version 0.19.1) (entered in the text editor of your choice):

from sklearn import datasets
iris = datasets.load_iris()
digits = datasets.load_digits()
print(digits.data)
digits.target
digits.images[0]

It is recommended to save this script with a .py file extension, but not necessary.

Once saved, the script can be tested on a login node by entering:

[NetID@cluster ~]$ python testscript.py

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