pgmpy
dodiscover
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| pgmpy | dodiscover | |
|---|---|---|
| 2 | 1 | |
| 2,617 | 57 | |
| 1.4% | - | |
| 8.0 | 3.8 | |
| 7 days ago | 7 days ago | |
| Python | Python | |
| MIT License | MIT License |
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pgmpy
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Use data from tables generated in python console,
No need to post the help, here is the DiscreteFactor class https://github.com/pgmpy/pgmpy/blob/eb65f40d2b32bf2ad971181333bb9ed7aefde907/pgmpy/factors/discrete/DiscreteFactor.py
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[D] Python toolboxes for probabilistic graphical model inference
I do know of a few promising toolboxes such as pgmpy, pymc3, and pyro, but have not used either of them (for this purpose) and am at a bit of a loss picking one to start with.
dodiscover
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Anyone that have worked with Causal discovery
I would check out https://github.com/py-why/dodiscover
What are some alternatives?
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
causal-learn - Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
statsmodels - Statsmodels: statistical modeling and econometrics in Python
causallift - CausalLift: Python package for causality-based Uplift Modeling in real-world business
scikit-learn - scikit-learn: machine learning in Python
cdci-causality - Python implementation of CDCI, a method to identify causal direction between two variables
CausalPy - A Python package for causal inference in quasi-experimental settings
rustworkx - A high performance Python graph library implemented in Rust.
pyhf - pure-Python HistFactory implementation with tensors and autodiff
Lottery-Simulation - This program can simulate a number of drawings in the Lottery (6 out of 49). The guesses and the draws are chosen randomly and the user can choose how many right guesses there should be (0-6). Then the program will run through the simulation as many times as it takes to get the exact number of correct guesses the user chose. The user can also choose how many times this should be repeated (the higher the number, the more accurate the result will be). Then the program will automatically calculate the average number of tries it took to get the chosen number of correct guesses and tell the user the chance of getting this certain number of correct guesses.
generalized-additive-models - Generalized Additive Models in Python.
auton-survival - Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events