similar to: Specifying a response variable in a Bayesian network

Hi everyone, I'm attempting to use the bnlearn package to calculate conditional probabilities, and I'm running into a problem when the "cpquery" function is used within a loop. I've created an example, shown below, using data included with the package. When using the cpquery function in a loop, a variable created in the loop ("evi" in the example) is not

Hi all I have built a Bayesian network using discrete data using the bnlearn package. When I try to run the cpquery function on this data it returns NaN for some some cases. 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

Dear Ross, This usually happen because you have parameters with a value of NaN in your network, because the data you estimate the network from are sparse and you are using maximum likelihood estimates. You should either 1) use simpler networks for which you can estimate all conditional distributions from the data or 2) use posterior estimates for the parameters. Cheers, Marco On 13 July

Hello: I have looked at the bnlearn and deal packages for infering bayesian network. Can anyone suggest any other suitable package for constructing bayesian gene regulatory network using gene expression data? Thanks! John [[alternative HTML version deleted]]

Hi all. I've recently uploaded a package (bnlearn) to CRAN. It builds fine on both Linux (32 and 64 bit) and Windows, but fails on MacOSX ix86 because of C90 vs C99 issues: http://www.r-project.org/nosvn/R.check/r-patched-macosx-ix86/bnlearn-00install.html Since I've no MacOSX machine at hand, I would like to ask you: why is C99 not the default for gcc on MacOSX ix86? Is it safe to

Hi, I need to classify, using Naive Bayes and Bayes Networks, and estimate their performance using cross validation. How can I do this? I tried the bnlearn package for Bayes Networks, althought I need to get more indexes, not only the error rate (precision, sensitivity, ...). I also tried the *e1071* package, but I could not find a way to do cross-validation. Thanks for everyone. Guilherme.

Hi every one I am working on shiny app using bnlearn for Bayesian networks and using r studio I get a fatal error and when I use R GUI I get this error ** caught segfault *** address 0xfffffffc0fcd6248, cause 'memory not mapped' Traceback: 1: .Call("mappred", node = node, fitted = fitted, data = data, n = as.integer(n), from = from, prob = prob, debug = debug) 2:

Hi Anyone have experience with very large datasets and the Bayesian Network package, bnlearn? In my experience R doesn't react well to very large datasets. Is there a way to divide up the dataset into pieces and incrementally learn the network with the pieces? This would also be helpful incase R crashes, because I could save the network after learning each piece. Thank you.

Hi, I am interested in using a bayesian network as a predictor (machine learning); however, I can't get any of the implementations (deal, nblearn) to learn & predict stuff. Shouldn't there also be probabilites for each node after the learning phase, how can I access these? Cheers, Stephan -- View this message in context:

Hi all, When I've been disassembling JIT-compiled functions I've noticed they all have the same three random instructions after them: bns- cr5,0xd04bbfe8 stfs f10,-16404(r3) stfs f10,-16404(r3) Is this meant to be there? Cheers, Gary -- http://gbenson.net/

I'm trying to run a logit model and plot the probability curve for a number of the important predictors. I'm trying to do this with the Effects package. df=data.frame(income=c(5,5,3,3,6,5), won=c(0,0,1,1,1,0), age=c(18,18,23,50,19,39), home=c(0,0,1,0,0,1)) str(df) md1 = glm(factor(won) ~ income + age + home, data=df,

On Thu, 2013-01-31 at 11:23 -0600, Bill Schmidt wrote: > On Thu, 2013-01-31 at 10:17 -0600, Bill Schmidt wrote: > > > > On Thu, 2013-01-31 at 09:42 -0600, Hal Finkel wrote: > > > ----- Original Message ----- > > > > From: "Bill Schmidt" <wschmidt at linux.vnet.ibm.com> > > > > To: llvmdev at cs.uiuc.edu > > > > Sent:

Dear R-help list: I have two related questions regarding the functions boot.strength and custom.strength in bnlearn. 1) I am using the following commands (on a set of continuous data, the example here run on fake data): > myblacklist<-data.frame(from=c("x1", "x1", "x1", "x2", "x2", "x2")) , to=c("x2",

On Thu, 2013-01-31 at 11:29 -0600, Bill Schmidt wrote: > On Thu, 2013-01-31 at 11:23 -0600, Bill Schmidt wrote: > > On Thu, 2013-01-31 at 10:17 -0600, Bill Schmidt wrote: > > > > > > On Thu, 2013-01-31 at 09:42 -0600, Hal Finkel wrote: > > > > ----- Original Message ----- > > > > > From: "Bill Schmidt" <wschmidt at

It could be stubs, data in text sections. Jump tables, constant pools, etc.? Are they ever executed? Evan On Jul 3, 2008, at 2:15 AM, Gary Benson wrote: > Hi all, > > When I've been disassembling JIT-compiled functions I've noticed they > all have the same three random instructions after them: > > bns- cr5,0xd04bbfe8 > stfs f10,-16404(r3) > stfs

On Jul 3, 2008, at 11:06 AMPDT, Evan Cheng wrote: > It could be stubs, data in text sections. Jump tables, constant pools, > etc.? Are they ever executed? > > Evan Almost certainly data not code. What are they in hex? > On Jul 3, 2008, at 2:15 AM, Gary Benson wrote: > >> Hi all, >> >> When I've been disassembling JIT-compiled functions I've noticed

I have the default installation of samba (2.0.5) that came with Caldera OL 2.3, but it doesn't seem to be starting up properly, nor is SWAT working. When I run the script 'samba start', I get the message "Starting samba: smbd nmbd", but when I check the running processes, only nmbd shows up. Running smbstatus gives me the message "Couldn't open status file

I'm exploring the simplex algorithm with a simple transportation problem of the form: minimize: 8a + 6b + 10c + 9d + 5e + 7f subject to the constraints: a + b + c = 11 d + e + f = 14 a + d = 10 b + e = 8 c + f = 7 I've implemented this in R (1.4.0 (2001-12-19), SunOS 5.7) as: require(boot) costs = c(8,6,10,9,5,7) constraints = c( 1,1,1,0,0,0, 0,0,0,1,1,1, 1,0,0,1,0,0,

hi, I''ve a normal Category model implemented with acts_as_tree (name, parent_id) that has_many :products (name, category_id). What I''m asking for is a method to fetch every product that belongs fall into a particular category and its children, eg: if I''m asking for a root node (/category/show/1) I need to display every product that have category_id = 1 AND every product

Hi R-users Is there any functions in R that can implement "expert systems"? The aim of an expert system is to produce a probable diagnosis for a patient with certain symptoms. In the classical expert system a mumber of "experts" are asked to make "statements" on the probabilities for different diseases when a combination of systems would appear. One typical