Project Summary
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.
In a Nutshell, PyMVPA...
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has a well established, mature codebase
maintained by a large development team
with increasing Y-O-Y commits -
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took an estimated 29 years of effort (COCOMO model)
starting with its first commit in May, 2007
ending with its most recent commit 2 months ago
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30 Day Summary Apr 16 2013 — May 16 2013
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12 Month Summary May 16 2012 — May 16 2013
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2013
Black Duck Software, Inc.
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