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Hello everyone, Excuse the title. I'm trying to do something very specific that goes against some common assumptions. I am aware of how Linux uses available memory to cache. This, in almost all cases, is desirable. I've spent years explaining to users how to properly read the free output. I'm now trying to increase VM density on host systems (by host, I mean the physical system, not

Dear R-users, While making a prediction using the randomForest function (package randomForest) I'm getting the following error message: "Error in predict.randomForest(model, newdata = CV) : No forest component in the object" Here's my complete code. For reproducing this task, please find my 2 data sets attached ( http://www.nabble.com/file/p17855119/data.rar data.rar ).

...spective, all Linux memory is > being "used?. Nope. VMware?s memory ballooning feature purposely keeps some of the guest?s RAM locked away from the kernel. This is where RAM comes from when another guest needs more physical RAM than it currently has access to: https://blogs.vmware.com/virtualreality/2008/10/memory-overcomm.html There are downsides. One is that pages locked up by the balloon driver aren?t being used by Linux?s buffer cache. But on the other hand, the hypervisor itself fulfills some of that role, which is why rebooting a VM guest is typically much faster than rebooting...

Hi all, First of all, I'm a novice R user (less that a week), so perhaps my code isn't very efficient. Using the MBoost package I created a model using the following command and saved it to a file for later use: model <- gamboost(fpfm,data=SampleClusterData,baselearner="bbs") # Creating a model save(model,file="model.RData") # Saving a model After this, during a

Dear R-user, I'm running a certain R script in DOS batch mode. Is there a way to prevent R from saving the workspace once this script is finished? I'm asking this because the resulting .RData file has the size of >70MB. I don't need this file since my script already writes the required output and this makes the whole process very slow (>15 minutes each time) FYI, my script:

Full_Name: Bas Zimmerman Version: 2.7.0 (2008-04-22) OS: Windows 2000 Pro SP 4 Eng Submission from: (NULL) (62.51.53.106) Running the following line of the R-code SurvivalEnsembles.R, part of the MBoost package results in a program crash: 'AMLrf <- cforest(I(log(time)) ~ ., data = AMLlearn, control = ctrl, weights = AMLw)' This package received a OK-check, see