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Analyzed 2 months ago. based on code collected 2 months ago.

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.

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In a Nutshell, PyMVPA...

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Python
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30 Day Summary

Jun 24 2016 — Jul 24 2016

12 Month Summary

Jul 24 2015 — Jul 24 2016
  • 290 Commits
    Down -148 (33%) from previous 12 months
  • 10 Contributors
    Down -2 (16%) from previous 12 months

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