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Hi, I write a package in Linux and ready to distribute, and I can install it in linux and run it. However, when I have install it in my Windows' R. I can not 'require' it. > is.element("grt", installed.packages()[,1]) [1] TRUE > require(grt) Loading required package: grt Failed with error: ‘'grt' is not a valid installed package’ Is there any pitfall

Hi, Jeremy and all This small patch lets pv ops guest handle machine check trap. When non fatal mce error happens, xen will inject vMCE# to the impacted pv ops guest. This patch allows pv ops guest could receive machine check trap and enter its own machine check handler. Thanks & Regards, Criping >From 5efc12fe8214d55e2becc2c4b6ec4a30531d7b60 Mon Sep 17 00:00:00 2001 From: Liping Ke

[Patch 4/4]: Xend interface for HVM S3 - extend "xm resume <domid>" to be able to S3 resume HVM domain. - when user issue "xm resume" command for HVM domain, xend will use xc lib API to call HVMOP_s3_resume hypercall. Note: it may not appropriate use xm resume for HVM s3, since xm resume is originally designed for save/restor purpose. It will be fine that

Dear R users: I have a dataset with two variables (>20000 observations, two samples from same subject) and I used "kernSur" from library(Genkern) to get a estimated bivariate density and corresponding plots as follows: new.data.normal<-data.normal[!is.na(data.normal[,2]),] x<-new.data.normal[,2] y<-new.data.normal[,3] op <- KernSur(x,y, xgridsize=50, ygridsize=50,

Dear R/Biocondutor users: I tried to merge two big affybatch data sets in R (under unix mainframe) and encounter the problems as following: combine2.3<-merge(combine2.1,TALL) Error: cannot allocate vector of size 409600 Kb I do not know what is the problem and how can i fix the problem. any suggustion will be appreciated. liping [[alternative HTML version deleted]]

Dear All, I am finding trouble trying to guild a Wrapper using random forest to evaluate the subsets: I do: nombi <- make_Weka_filter("weka/filters/supervised/attribute/AttributeSelection") datbin<- nombi(gene ~., data=X1X2X4X5W, control =Weka_control( S=list("weka.attributeSelection.GeneticSearch"), E=list("weka.attributeSelection.WrapperSubsetEval"),B

ioemu-remote: The device model needs to write in the ACPI tables when it wakes up from S3 state. Signed-off-by: Jean Guyader <jean.guyader@eu.citrix.com> -- Jean Guyader _______________________________________________ Xen-devel mailing list Xen-devel@lists.xensource.com http://lists.xensource.com/xen-devel

Dear Sir / Madam, I am using R Programming Language Version 2.15.1 (2012-06-22) for sometime in a 32 bit PC running Windows OS (Platform: i386-pc-mingw32/i386 (32-bit)). During the execution / interpretation of the R script, sometimes it is found that behavior of the program is not consistent with the program structure. For example, it has been seen that, even if a condition inside an IF

Hello all, I am attempting to run an R script that makes use of RWeka. I am running SuSE Linux 9.3 with Java 1.5.0_06, R version 2.2.1, Weka 3-4-7, and Rweka 0.2-1. CLASSPATH="/usr/local/weka-3-4-7/weka.jar:/usr/local/JGR/JGR.jar" I receive the error: NewObject("weka/core/Instances","(Ljava/io/Reader;)V",...) failed Exception in thread "main"

Dear All, I'd like to use Weka functions that are not implemented (do not have interface) in RWeka, like the Remove function and others in the future! The .java() functionality is for that purpose but I haven't seen any example with Weka functions. Could anyone give me hand in how to do it? For instace if I want to use the weka.filters.unsupervised.attribute.Remove? 1. in the R console,

Le jeudi 09 f?vrier 2012 ? 15:31 +0200, Kari Ruohonen a ?crit : > Hi, > I am trying to replicate a training of AttributeSelectedClassifier with > CFsSubsetEval, BestFirst and NaiveBayes that I have initially done with > Weka. Now, I am trying to use RWeka in R. > > I have a problem of passing arguments to the CfsSubsetEval, BestFirst > and NaiveBayes. I have first created an

Hi, All Following 4 patches are for enabling CMCI of Intel CPUs in XEN. --------------------------------------------------------------------------- Patch 1: remove_intel_mce_old.patch is to remove old p4/p6 files. The reason is that machine check architecture for Intel families including p4/p6/latest are similar. We need not keep duplicated codes. Patch 2: change_stop_machine_run.patch changes

Hello, I have some trouble in achieving the desired parametrisation for the weka classifier functions, using the package RWeka. The problem is, that the functions result=classifier(formula, data, subset, na.action, control = Weka_control(mycontrol)) do not seem to be manipulated by the mycontrol- arguments Perhaps this should be resepected via the handlers- argument , but the

I am familiar with the rpart and tree packages for classification and regression trees. However, quite a bit of the research in the transportation community relating to decision trees uses the C4.5 family of algorithms by Quinlan. Are there any plans to make a C4.5 (or a derivative of it) available to R? If not, then I might use the WEKA Java package ( http://www.cs.waikato.ac.nz/ml/weka) that

Hello, I have a trained Back Propagation Neural Network model in weka. I would like to re-evaluate the NN using R with a given input. How can I do this? I could not find an example of RWeca that applies to NN Thanks, Rui

Hello, I have two questions concerning the RWeka package: 1.) First question: How can one perform a cross validation, -say 10fold- for a given data set and given model ? 2.) Second question What is the correct syntax for the parametrization of e.g. Kernel classifiers interface m1 <- SMO(Species ~ ., data = iris, control =

Hello All, I am trying to carry out variable reduction. I do not have information about the dependent variable, and have only the X variables as it were. In selecting variables I wish to keep, I have considered the following criteria. 1) Percentage of missing value in each column/variable 2) Variance of each variable, with a cut-off value. I recently came across Weka and found that there is an

hi all i would like to know if anyone has a reference on how one would place the "bands" on the pp plot. i want to test whether or not a certain data set comes from a particular distribution (not normal). i've already plotted F(X(j)) vs j/(n+1) where F(x) is the cum dist function, X(j) is the j'th order statistic and n is the sample size. a goole search gave arb references

https://bugzilla.netfilter.org/show_bug.cgi?id=1144 Bug ID: 1144 Summary: set add always returns false or otherwise ends evaluation Product: nftables Version: unspecified Hardware: x86_64 OS: All Status: NEW Severity: normal Priority: P5 Component: kernel

Hi, I want to save a RWeka model into a file, in order to retrive it latter with a load function. See this example: library(RWeka) NB <- make_Weka_classifier("weka/classifiers/bayes/NaiveBayes") model<-NB(formula,data=data,...) # does not run but you get the idea save(model,file="model.dat") # simple save R command # ... load("model.dat") # load the model