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Analyzed 4 months ago. based on code collected 4 months ago.

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.

Tags

classifiers machine_learning science development education data_mining analysis framework python library research neuroscience pattern_recognition

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Languages

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Python
94%
7 Other
6%

30 Day Summary

Oct 5 2016 — Nov 4 2016

12 Month Summary

Nov 4 2015 — Nov 4 2016
  • 218 Commits
    Down -287 (56%) from previous 12 months
  • 6 Contributors
    Down -8 (57%) from previous 12 months