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pypi.org : trilearn
Bayesian predictive classification and structure learning in decomposable graphical models using particle Gibbs.
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purl: pkg:pypi/trilearn
Keywords: bayesian-inference, bayesian-statistics, classification, covariance-selection, decomposable-graphical-models, decomposable-graphs, gaussian-graphical-models, log-linear-model, machine-learning, markov-networks, predictive-modeling, sequential-monte-carlo
License: Apache-2.0
Latest release: 4 months ago
First release: over 5 years ago
Dependent repositories: 1
Downloads: 33 last month
Stars: 12 on GitHub
Forks: 5 on GitHub
Docker dependents: 1
Docker downloads: 292
Total Commits: 152
Committers: 5
Average commits per author: 30.4
Development Distribution Score (DDS): 0.25
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Last synced: 10 days ago