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Currently, the code repository supports only discrete random variables. The code should be extended to include continuous random variables. Support for some common probability density functions (for eg: Normal distribution, geometric distribution etc. ) must also be added.
The text was updated successfully, but these errors were encountered:
Hi @belerico
As a first step, I would like to suggest you go through the probability module from the code repo. When we work with any particular Bayesian Network, the random variables at various nodes can be both discrete as well as continuous. At present, we have assumed that the random variables represented by the nodes are discrete and hence we represent their conditional probability distributions using a categorical table. The final aim should be to enable the use of continuous random variables in the Bayesian Network.
We can begin with the support of a Gaussian Random Variable and add other distributions later on. Feel free to ping if you need any help.
Currently, the code repository supports only discrete random variables. The code should be extended to include continuous random variables. Support for some common probability density functions (for eg: Normal distribution, geometric distribution etc. ) must also be added.
The text was updated successfully, but these errors were encountered: