similar to: Random Seed Location

In case you don't get an answer from someone more knowledgeable: 1. I don't know. 2. But it is possible that other packages that are loaded after set.seed() fool with the RNG. 3. So I would call set.seed just before you invoke each random number generation to be safe. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking

On Mon, Feb 26, 2018 at 3:25 PM, Gary Black <gwblack001 at sbcglobal.net> wrote: (Sorry to be a bit slow responding.) You have not supplied a complete example, which would be good in this case because what you are suggesting could be a serious bug in R or a package. Serious journals require reproducibility these days. For example, JSS is very clear on this point. To your question >

Thank you, everybody, who replied! I appreciate your valuable advise! I will move the location of the set.seed() command to after all packages have been installed and loaded. Best regards, Gary Sent from my iPad > On Mar 4, 2018, at 12:18 PM, Paul Gilbert <pgilbert902 at gmail.com> wrote: > > On Mon, Feb 26, 2018 at 3:25 PM, Gary Black <gwblack001 at sbcglobal.net> >

The following helps identify when .GlobalEnv$.Random.seed has changed: rng_tracker <- local({ last <- .GlobalEnv$.Random.seed function(...) { curr <- .GlobalEnv$.Random.seed if (!identical(curr, last)) { warning(".Random.seed changed") last <<- curr } TRUE } }) addTaskCallback(rng_tracker, name = "RNG tracker") EXAMPLE: >

On 04/03/2018 5:54 PM, Henrik Bengtsson wrote: > The following helps identify when .GlobalEnv$.Random.seed has changed: > > rng_tracker <- local({ > last <- .GlobalEnv$.Random.seed > function(...) { > curr <- .GlobalEnv$.Random.seed > if (!identical(curr, last)) { > warning(".Random.seed changed") > last <<- curr

On Sun, Mar 4, 2018 at 3:23 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 04/03/2018 5:54 PM, Henrik Bengtsson wrote: >> >> The following helps identify when .GlobalEnv$.Random.seed has changed: >> >> rng_tracker <- local({ >> last <- .GlobalEnv$.Random.seed >> function(...) { >> curr <- .GlobalEnv$.Random.seed

When I import a simple dataset, run LDA, and then try to use the model to forecast out of sample data, I get a forecast for the training set not the out of sample set. Others have posted this question, but I do not see the answers to their posts. Here is some sample data: Date Names v1 v2 v3 c1 1/31/2009 Name1 0.714472361 0.902552278 0.783353694 a 1/31/2009 Name2 0.512158919 0.770451596

Hi All, I'm a newbie and have two questions. Please pardon me if they are very basic. 1. I'm using a regression tree to predict the selling prices of 10 new records (homes). The following code is resulting in an error message: pred <- predict(model, newdata = outOfSample[, -6]) The error message is: Error in model.frame.default(Terms, newdata, na.action = na.action, xlev =

On Sat, Feb 24, 2018 at 01:16:27PM -0600, Gary Black wrote: > Hi All, > > I'm a newbie and have two questions. Please pardon me if they are very basic. > > > 1. I'm using a regression tree to predict the selling prices of 10 new records (homes). The following code is resulting in an error message: pred <- predict(model, newdata = outOfSample[, -6]) > >

Hi everyone I am trying to do cross validation (10 fold CV) by using e1071:svm method. I know that there is an option (?cross?) for cross validation but still I wanted to make a function to Generate cross-validation indices using pls: cvsegments method. ##################################################################### Code (at the end) Is working fine but sometime caret:confusionMatrix

I've been updating a package and, when installing a local devel version, I get an error "object 'confusionMatrix' not found whilst loading namespace". Looking around online, it appears that this might be related to loading a specific RData file, but it doesn't seem to be the case AFAICT. I've installed the devel version in the last week without issues and the

Hello, As obtained from a table svyglm clasificaion, sensitivity and specificity. The funtion ConfusionMatrix () of the library (caret) gives these results but not how to apply it to svyglm. thanks [[alternative HTML version deleted]]

Dear R-colleagues, another question from a newbie: I am creating a lot of simple pivot-charts from my raw data using the reshape-package. In these charts we have medical doctors judging videos in the columns and the videos they judge in the rows. Simple example of chart/data.frame "input" with two categories 1/0: video 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 1 1 0 0

Hi. Can anyone suggest how to use the output of pcaNNet() to construct a confusion matrix possibly using confusionMatrix()? Thank you. -- View this message in context: http://www.nabble.com/pcaNNet-confusion-tp24422000p24422000.html Sent from the R help mailing list archive at Nabble.com.

ggplot2 ------------------------------------------------------------ ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and avoid bad parts. It takes care of many of the fiddly details that make plotting a hassle (like drawing legends) as well as providing a powerful model of graphics that makes it easy to produce

ggplot2 ------------------------------------------------------------ ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and avoid bad parts. It takes care of many of the fiddly details that make plotting a hassle (like drawing legends) as well as providing a powerful model of graphics that makes it easy to produce

Hi R users, I am getting the following error when using the splsda function in R v2.12.1: "Error in switch(classifier, logistic = { : EXPR must be a length 1 vector" What does this mean and how do I fix this? Thank you in advance! Best, Savi

Hello, When evaluating different learning methods for a categorization problem with the (really useful!) caret package, I'm getting confusing results from the Kappa computation. The data is about 20,000 rows and a few dozen columns, and the categories are quite asymmetrical, 4.1% in one category and 95.9% in the other. When I train a ctree model as: model <- train(dat.dts,

*Hi, *Does anyone know how can I show an *ROC curve for R-SVM*? I understand in R-SVM we are not optimizing over SVM cost parameter. Any example ROC for R-SVM code or guidance can be really useful. Thanks, Angel. [[alternative HTML version deleted]]

Dear all, I have a couple of short noob questions for whoever can take them. I'm from a very non-stats background so sorry for offending anybody with stupid questions ! :-) I have been using logistic regression care of glm to analyse a binary dependent variable against a couple of independent variables. All has gone well so far. In my work I have to compare the accuracy of analysis to a C4.5