search for: bnlearn

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 def...

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. [[alt...

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 (...

...estimate all conditional distributions from the data or 2) use posterior estimates for the parameters. Cheers, Marco On 13 July 2017 at 06:29, Ross Chapman <rosspjchapman at gmail.com> wrote: > 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 gra...

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...

I'm trying to teach myself about Bayesian Networks and am working with the following data and the bnlearn package. I understand the conceptual aspects of BNs, but I'm not sure how to specify the response variables in R when constructing a dag plot. I've cecked ?hc and done numerous google searches without luck. Can anyone help? library("bnlearn") library("Rgraphviz") dat=...

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", "n3", "n4&q...

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. [[alternative HTML version deleted]]

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 = fro...

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:

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 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

...vailable to watch: http://blog.revolutionanalytics.com/2017/05/watch-rfinance-2017.html A review of some of the R packages and projects implemented at the 2017 ROpenSci Unconference: http://blog.revolutionanalytics.com/2017/05/runconf17.html An example of applying Bayesian Learning with the "bnlearn" package to challenge stereotypical assumptions: http://blog.revolutionanalytics.com/2017/05/who-is-the-caretaker.html Data from the Billboard Hot 100 chart used to find the most popular words in the titles of pop hits: http://blog.revolutionanalytics.com/2017/05/love-is-all-around.html Micr...

...tler http://crantastic.org/packages/TunePareto Generic methods for parameter tuning of classification algorithms using multiple scoring functions Updated packages ---------------- ade4 (1.4-16), adlift (1.2-3), AICcmodavg (1.08), aqp (0.94-1), aspace (2.5), aspace (2.4), BioStatR (1.0.2), bnlearn (2.2), caret (4.54), caret (4.53), clustTool (1.6.5), coarseDataTools (0.3), constrainedKriging (0.1.2), DEMEtics (0.8.1), emdbook (1.2.2.1), FitAR (1.80), fpc (2.0-2), futile.paradigm (1.0.1), futile.paradigm (1.0.2), gamlss (4.0-3), gamlss.add (4.0-1), gamlss.data (4.0-1), genoPlotR (0.5.1), GEOm...

CRAN (and crantastic) updates this week New packages ------------ * Bergm (1.0) Alberto Caimo http://crantastic.org/packages/Bergm Functions implementing Bayesian estimation for exponential random graph models via exchange algorithm Updated packages ---------------- lmtest (0.9-26), logcondens (1.3.5), MTSKNN (0.0-4), pmml (1.2.21), r2lUniv (0.9.4), rattle (2.5.11), rgdal (0.6-23),

...ameters you want to analyse, build your regulated time series, perform analysis and read the results all in one easy to use interface. Statistical analysis call other package function such as Kendall tests (wq package) or cusum function (Pastec package). Updated packages ---------------- bnlearn (2.9), catspec (0.96), cda (1.1.3), clue (0.3-44), coin (1.0-21), crs (0.15-13), cvTools (0.3.0), Deducer (0.6-2), directlabels (2.4), doRNG (1.2.1), dplR (1.5.3), DSL (0.1-1), eqtl (1.1-7), ergm (3.0-1), ergm.userterms (3.0-1), fda.usc (0.9.6), frailtypack (2.2-22), games (1.0-5), gdsfmt (0.9.6),...

...0-1), arm (1.3-05), aroma.affymetrix (1.6.0), aroma.core (1.6.0), asbio (0.3-10), ascii (0.7), automap (1.0-7), bayesmix (0.7-1), bbmle (0.9.5.1), bcp (2.2.0), bear (2.5.3), bibtex (0.2-0), bifactorial (1.4.4), bigmemory (4.2.3), binGroup (1.0-5), biOps (0.2.1.1), bipartite (1.12), blighty (3.1-0), bnlearn (2.1.1), bootruin (1.0-156), brglm (0.5-5), cairoDevice (2.13), caret (4.43), catspec (0.95), cgh (1.0-7.1), cluster (1.13.1), clusterSim (0.38-1), cmprskContin (1.6), coarseDataTools (0.2), coin (1.0-12), copula (0.9-7), corrplot (0.30), cshapes (0.2-4), ctv (0.6-0), cudaBayesreg (0.3-6), dagR (1....

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",