DiscreteBayesNet - CPD order and named categories

[drbenvincent]

I am starting a project using discrete Bayes Nets and I am hoping to use this package, rather than one of the python packages (eg pomegranate or pgmpy). But I have a few questions...

I managed to get a simple example working (made up numbers), with

bn = DiscreteBayesNet()
push!(bn, DiscreteCPD(:smoke, [0.25,0.75]))
push!(bn, DiscreteCPD(:covid, [0.1,0.9]))
push!(bn, DiscreteCPD(:hospital, [:smoke, :covid], [2,2], 
        [Categorical([0.9,0.1]),
         Categorical([0.2,0.8]),
         Categorical([0.7,0.3]),
         Categorical([0.01,0.99]),
        ]))

Could I request a little more information in the documentation about the way in which this CPD is coded? Eventually I was able to figure it out by asking for the CPD table with table(bn, :hospital)

but I'd definitely say more documentation here would help people out.

Secondly, is there a way to name the levels that each node can take? From the docs I attempted a guess at something like this...

bn = DiscreteBayesNet()
push!(bn, DiscreteCPD(:smoke, NamedCategorical([:yes, :no], [0.25, 0.75])))
push!(bn, DiscreteCPD(:covid, NamedCategorical([:yes, :no], [0.1, 0.9])))
push!(bn, DiscreteCPD(:hospital, [:smoke, :covid], [2,2], 
        [NamedCategorical([:yes, :no], [0.9, 0.1]),
         NamedCategorical([:yes, :no], [0.2, 0.8]),
         NamedCategorical([:yes, :no], [0.7, 0.3]),
         NamedCategorical([:yes, :no], [0.01, 0.99])]))

but no luck. Any pointers or updates to the docs on this would be very much appreciated.
Ben

[mathlawguy]

I too would be interested in either getting NamedCategorical to work with DiscreteBayesNet or having that feature added. As I understand it, the infer function works only with DiscreteBayesNet. Since mostly what I want to do is "infer," having the ability to use NamedCategorical would help the clarity of my programs.

[mykelk]

@dwijenchawra is this issue of interest to you?