Evaluating dependencies among random variables.
depynd is a Python library for evaluating dependencies among random variables from data. It supports learning statistical dependencies for one-to-one, one-to-many, and many-to-many relationships, where each one corresponds to
- mutual information (MI) estimation,
- feature selection, and
- graphical model structure learning,
respectively. Specifically, depynd supports MI estimation for discrete-continuous mixtures, MI-based feature selection, and structure learning of undirected graphical models (a.k.a. Markov random fields).
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