Libraries for Bayesian network inference with continuous data

Question

Libraries for Bayesian network inference with continuous data

Zebra Propulsion Lab

2019年3月5日 19:05

Is there any good libraries that allow me to:

Construct a Bayesian network manually
Specify the conditional probabilities with any continuous PDF, not just Guassian
Perform inference, either exact or approximate

I looked at the following libraries so far, none of them meet the 3 requirements:

pgmpy: only work on discrete distribution or linear Guassian distribution
bnlearn: same as pgmpy
gRain: only discrete distribution
Huggin: only discrete distribution and Guassian
deal: no support for inference
abn: same as deal
libpgm: only discrete distribution and Guassian

Topic graphical-model bayesian-networks

Category Data Science

ashudeep21 · Accepted Answer · 2019年3月5日 19:05

1

ashudeep21 answered at 2019年3月5日 19:05

You can use pymc3. I am pretty sure it works for all the 3 requirements. http://pymc-devs.github.io/pymc3/

John Q · Accepted Answer · 2019年2月25日 14:37

1

John Q answered at 2019年2月25日 14:37

Also have look at Genie (GUI) and SMILE (Lib) from BayesFusion (formerly University of Pittsburgh). Academic usage is free, but registration required.

knb · Accepted Answer · 2017年4月12日 09:01

Not a library, but a interactive GUI based tool is "samiam" (Sensitivity Analysis Modeling Inference and More) from a research group at UCLA.

I am not sure about your "continuous PDFs" requirement, whether it's possible to define them inside the samiam GUI.

samiam is free to download, but registration is required.

The size of the software is small, but java-based (ok, the jvm is not that small).

For API-access, you might call functions inside the inflib.jar file.

There also exists a "Batch tool" and a "Code Bandit" (code generator). Haven't used any of them.

Libraries for Bayesian network inference with continuous data

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