Project details for PyMVPA Multivariate Pattern Analysis in Python

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Version:
0.4.5
Submitter:
yarikoptic
Author(s):
Michael Hanke , Yaroslav Halchenko , Per B. Sederberg , Emanuele Olivetti
Posted:
2 October 2010
Last Updated:
2 October 2010
Open Source License:
mit
Programming Language(s):
python, c

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Screenshot PyMVPA Multivariate Pattern Analysis in Python 0.4.5

by yarikoptic - October 2, 2010, 16:51:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

view ( today), download ( today ), 3 comments, 0 subscriptions

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Description:

Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression, GPR. RFE, I-RELIEF), and bindings to external ML libraries (libsvm, shogun, R). While it is not limited to neuroimaging data (e.g. FMRI) it is eminently suited for such datasets.

It is actively developed project, thus you might better off trying it from the version control system which contains 0.5 development going forward. See http://dev.pymvpa.org for the upcoming website/documentation. Please see documentation on how to obtain and "build" from sources.

Changes to previous version:

0.4.5 (Fri, Oct 01 2010) (Total: 27 commits)

A bugfix release 

* Fixed (13 BF commits):
      o Compatible with LIBSVM >= 2.91 (Closes: #583018)
      o No string exceptions raised (Python 2.6 compatibility)
      o Setting of shrinking parameter in sg interface
      o Deducing number of SVs for SVR (LIBSVM)
      o Correction of significance in the tails of non-parametric tests
* Miscellaneous:
      o Development repository moved to http://github.com/PyMVPA/PyMVPA
BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Agnostic
Data Formats: None
Tags: Shogun, Python, Eeg, Classification, Regression, Support Vector Machines, K Nearest Neighbor Classification, Pca, Rfe, Neuroscience, Fmri, Framework, Gpr, Lars, Smlr, Meg
Archive: download here

Comments

Yaroslav Halchenko (on May 18, 2008, 17:07:37)
It is actively developed project at the moment, thus it is preferable to don't rely on releases but rather use master branch of git repository mentioned on the project homepage
Yaroslav Halchenko (on September 8, 2009, 20:21:46)
0.4.3 release update
Yaroslav Halchenko (on September 8, 2009, 20:29:35)
updated entry to don't be treated as PRE

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