pgmpy: Probabilistic Graphical Models using Python 论文

2015Proceedings of the Python in Science Conferences引用 229
Computational Physics and Python ApplicationsNeural Networks and Applications

摘要

Probabilistic Graphical Models (PGM) is a technique of compactly representing a joint distribution by exploiting dependencies between the random variables. It also allows us to do inference on joint distributions in a computationally cheaper way than the traditional methods. PGMs are widely used in the field of speech recognition, information extraction, image segmentation, modelling gene regulatory networks.

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