Hi all
I have created a Bayes network with 14 nodes using the bnlearn package and
want to explore the conditional probabilities for specific node with a given
set of evidence using the cpquery() command.
I find that repeating the command gives very different results for the same
set of evi
Hi all
I have a problem with the cpquery function in the bnlearn package.
I have constructed a hybrid network (using a mix of continuous and discrete
variables).
The network is named "fitted".
I am interested in predicting the probability of observing a value greater
that a particul
Hi Marco
Thanks again for your comments.
First, I used the term "EST = y" in my original query as a shorthand, I have
used the terms "K1", "M1", and "M2" for all actual queries.
If I might expand on the outputs I am getting, I have run predict for the
term "ABW" on a data vector with th
Hi all,
I have created a TAN network using bnlearn in R using the commands:
TAN <- tree.bayes(training.data,"classFFB")
fitted <- bn.fit(TAN,training.data,method="bayes")
where training.data is a dataframe with 6 variables.
I have produced a plot of the network using graphviz.plot:
Hi Marco
Thanks for your quick response
>-Original Message-
>From: Marco Scutari [mailto:marco.scut...@gmail.com]
>Sent: Monday, 29 February 2016 8:24 PM
>To: ross.chap...@ecogeonomix.com
>Cc: r-help
>Subject: Re: [R] bnlearn and TAN network
>
>Hi Ross,
>
>On 29 February 2016 at 08:46,
Hi all,
I am having a problem running the "impute" function from the bnlearn
package.
I have tried running the example in the documentation as follows:
with.missing.data = gaussian.test
with.missing.data[sample(nrow(with.missing.data), 500), "F"] = NA
fitted = bn.fit(model2network("[
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