[R] bnlearn and cpquery
rosspjchapman at gmail.com
Thu Jul 13 07:29:12 CEST 2017
I have built a Bayesian network using discrete data using the bnlearn
When I try to run the cpquery function on this data it returns NaN for some
Running the cpquery in debug mode for such a case (n=10^5, method="lw")
creates the following output:
generated a grand total of 1e+05 samples.
> event has a probability mass of 14982.37 out of NaN (p = NaN).
The cpquery command takes the following structure:
evidence=list(GK_class = "ModHi",
GTh_class = "Lo",
GU_class = "Lo",
El_class = "Hi",
E50_class = "Med",
E150_class = "Med"
n=10^5, method = "lw", debug=TRUE)
Similarly, when I try to run the predict method on the same data, it returns
the following warning:
In map.prediction(node = node, fitted = object, data = data, n =
dropping 38073 observations because generated samples are NAs.
Could you advise me why these queries are generating NaN values, and how
they might be resolved.
The session info is as follows:
R version 3.4.1 (2017-06-30)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
 LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252
 LC_NUMERIC=C LC_TIME=English_Australia.1252
attached base packages:
 stats graphics grDevices utils datasets methods base
other attached packages:
loaded via a namespace (and not attached):
 compiler_3.4.1 tools_3.4.1
Many thanks in advance
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