similar to: bnlearn and very large datasets (> 1 million observations)

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 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

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")

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",

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:

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, 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:

On 9/29/2017 3:37 PM, Rolf Turner wrote: > On 30/09/17 07:45, JLucke at ria.buffalo.edu wrote: > > <SNIP> > >> >> The conceptual paradigm for R is only marginally commensurate with >> that of >> standard statistical software. >> You must immerse yourself in R to become proficient. > > Fortune nomination. For newer list members wondering what

I wish to second this approach to learning R. I tried for several years to translate other stat programs or provide parallel analyses with R. This dabbling-in-R approach did not work . When a transferred to a research unit that could ill afford commercial software, I devoted my entire time to doing everything in R. This was a difficult learning process, but I eventually became proficient

Hi all, When configuring Asterisk with an ISDN card, it will at one point become necessary to select the LBO (Line Build-Out) value. This is an integer (0-7) that is determined by the length of the cable and is selected from the following table. Many of us are familiar with it: CSU (dB) DSX-1 (feet) ------------------------------- 0 0 0?133 1

On 30/09/17 07:45, JLucke at ria.buffalo.edu wrote: <SNIP> > > The conceptual paradigm for R is only marginally commensurate with that of > standard statistical software. > You must immerse yourself in R to become proficient. Fortune nomination. cheers, Rolf -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276

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

I have a Master's student working on a project which involves estimating parameters of a certain model via maximum likelihood, with the maximization being done via optim(). A phenomenon has occurred which I am at a loss to explain. If we use certain pairs of starting values for optim(), it simply returns those values as the ``optimal'' values, although they are definitely not

Since 2008, Microsoft (formerly Revolution Analytics) staff and guests have written about R every weekday at the Revolutions blog (http://blog.revolutionanalytics.com) and every month I post a summary of articles from the previous month of particular interest to readers of r-help. In case you missed them, here are some articles related to R from the month of May: Many interesting presentations

On 29 April 2019 at 15:03, Kurt Hornik wrote: | >>>>> Johannes Ranke writes: | | > Am Montag, 29. April 2019, 13:44:03 CEST schrieb Kurt Hornik: | >> >>>>> Johannes Ranke writes: | >> Thanks. You may have seen that with current gfortran in | >> testing/unstable, there are problems with the R BLAS/LAPACK API entries | >> using a Fortran

Dear List the other day, I had my yearly staff interview with my Head of Department. Under my list of publications, I included a document which I wrote (R-and-octave.txt) that ended up in the "contributed docs" section of CRAN. Unfortunately, neither my HoD nor the personnel person were terribly impressed with it, even though its preparation time was commensurate with many of my (co

On Tue, Mar 4, 2014 at 6:17 PM, Chandler Carruth <chandlerc at google.com>wrote: > On Tue, Mar 4, 2014 at 1:04 PM, Mark Seaborn <mseaborn at chromium.org>wrote: > >> The PNaCl project has implemented various IR simplification passes that >> simplify LLVM IR by lowering complex features to simpler features. We'd >> like to upstream some of these IR passes