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.
- Homepage: https://scikit-learn.org/
Scikit-Learn is open to all HPRC users.
Anaconda and Scikit-Learn Packages
TAMU HPRC currently supports the user of Scikit-Learn though the Anaconda modules. There are a variety of Anaconda modules available on Ada and Terra. An anaconda module may provides different version of scikit-learn. It is recommend to use the latest Anaconda module.
To access scikit-learn on Ada or Terra:
[NetID@terra ~]$ module load Anaconda/3-188.8.131.52
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
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@terra ~]$ python testscript.py