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Graphical model analysis toolbox.

Project description

PGM

Build Status Documentation Status PyPI version License: MIT

Probabilistic graphs: Representation, Learning, and Inference

Features

  • Representation
    • Bayesian Network Representation
    • Linked List BN Representation
    • Linked List MN Representation
    • Conditional Estimation
    • Marginal Estimation
    • Joint Estimation
  • Inference
    • Metropolis-Hastings algorithm
    • Gibbs Sampling on 2d grid
    • Generalized Gibbs Sampling
    • Message Parsing and BP
    • Loopy BP
    • VE
    • Causal Interventions
  • search methods
    • DFS
    • BFS
  • Additional
    • Finding Active Trails
    • Max clique size and clique node
    • Calculate tree-width
  • Learning
  • Miscellaneous
    • Random BN and MN generation

Installation

pip install ppgm

Contact

Project details


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ppgm-0.0.3.tar.gz (10.0 kB view hashes)

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