A Python data structure to encapsulate a machine learning dataset greatly suited for neuroimaging applications (or any other domain), where each sample needs to be uniquely identified with a subject ID (or something similar). Key-level correspondence across data, labels (1 or 2), classnames (‘healthy’, ‘disease’) and the related helps maintain data integrity, in addition to enabling traceback to original sources from where the features have been originally derived.
Please refer to the notebook for an illustration of the usage: https://github.com/raamana/pyradigm/blob/master/PyradigmExample.ipynb
TODO: Figure out how to actually get changelog content.
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