PGM
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
- Avinash Kori (koriavinash1@gmail.com)
1 maintainer
Metadata
1 maintainer
Release files for ppgm 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ppgm-0.0.4.tar.gz | 10.9 kB | Details |
Release files / ppgm-0.0.4.tar.gz
| Download URL | ppgm-0.0.4.tar.gz |
|---|---|
| Size | 10.9 kB |
| Tags | Source |
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44172374e4191562a70246bbda0d27d52248a994f2f512eb8ebf994de826ceef
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twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.3
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