Machine Learning Py (mlpy)

author: Davide Albanese, Fondazione Bruno Kessler
published: Dec. 20, 2008,   recorded: December 2008,   views: 1700
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

We introduce mlpy, a high-performance Python package for predictive modeling. It makes extensive use of NumPy to provide fast N-dimensional array manipulation and easy integration of C code. Mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. The package includes tools to measure stability in sets of ranked feature lists, of special interest in bioinformatics for functional genomics, for which large scale experiments with up to 106 classifiers have been run on Linux clusters and on the Grid.

See Also:

Download slides icon Download slides: mloss08_albanese_mlp_01.pdf (407.2 KB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: