Scikit-learn

Category

Python, library, machine learning

Description

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Available versions (Euler, old software stack)

Legacy versions	Supported versions	New versions
	0.16.1, 0.17.1	0.18.1, 0.18.2, 0.20.3

Please note that this page refers to installations from the old software stack. There are two software stacks on Euler. Newer versions of software are found in the new software stack.

Environment modules (Euler, old software stack)

Version	Module load command	Additional modules loaded automatically
0.16.1	module load gcc/4.8.2 python/3.3.3	openblas/0.2.13_seq
0.17.1	module load gcc/4.8.2 python/2.7.6	openblas/0.2.13_seq
0.17.1	module load new gcc/4.8.2 python/2.7.9	openblas/0.2.13_seq
0.18.1	module load new gcc/4.8.2 python/2.7.12	openblas/0.2.13_seq
0.18.1	module load new gcc/4.8.2 python/2.7.13	openblas/0.2.13_seq sqlite/3.15.0
0.18.1	module load new gcc/4.8.2 python/3.4.3	openblas/0.2.13_seq
0.18.1	module load new gcc/4.8.2 python/3.6.0	openblas/0.2.13_seq sqlite/3.15.0
0.20.3	module load new gcc/4.8.2 python/3.7.1	openblas/0.2.13_seq

Please note that this page refers to installations from the old software stack. There are two software stacks on Euler. Newer versions of software are found in the new software stack.

Interactive session

You can start an interactive scikit-learn session on the login nodes by loading the corresponding modules and starting the Python interpreter.

[sfux@eu-login-04 ~]$ module load new gcc/4.8.2 python/3.6.0
Autoloading openblas/0.2.13_seq and sqlite/3.15.0
[sfux@eu-login-04 ~]$ python
Python 3.6.0 (default, Feb 10 2017, 09:00:08) 
[GCC 4.8.2] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import sklearn
>>> sklearn.__version__
'0.18.1'
>>> 

Please note that you should use interactive sessions only for very short test that do not use a lot of CPU capacity. You have to submit all other computations as a batch job.

How to submit a job

Scikit-learn is a Python package. Please check Python page for information about how to submit a Python batch job.

License information

3-clause BSD license

Links

http://scikit-learn.org/stable

https://en.wikipedia.org/wiki/Scikit-learn
https://pypi.python.org/pypi/scikit-learn
https://github.com/scikit-learn/scikit-learn
http://machinelearningmastery.com/a-gentle-introduction-to-scikit-learn-a-python-machine-learning-library
https://www.springboard.com/blog/beginners-guide-neural-network-in-python-scikit-learn-0-18