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.
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In a Nutshell, PyMVPA...
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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 about 8 years ago
MIT License
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30 Day SummaryMar 19 2024 — Apr 18 2024
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12 Month SummaryApr 18 2023 — Apr 18 2024
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