similar to: ggplot rank stack bar automatically.

Hi all, I apologize for the ignorance implicit in this question, but I'm having a hard time figuring out how R functions work. For example, if I wanted to write a function to compute a variance, I would do something like >my.var <- function(x) (sum(((x-mean(x)))^2))/(length(((x-mean(x))) ^2)-1) And this seems to work, e.g., > my.var(V1) [1] 116.1 > var(V1) [1] 116.1

Is the machine your configuring permissions on joined to the domain that samba is using? That's the last of my advice/querying ability, since DNS is on a proper server (and I assume pointed to the right address on the client as well) On Apr 21, 2016 11:00 PM, "Stefan Fuhrmann" <stefan at fuhrmann.homedns.org> wrote: > Hallo Luke, > > > okay, I attached the

Is there any way to request WEBrick to shutdown besides hitting CTRL-C at the console? I''m looking for, perhaps, a script/shutdown command, or perhaps a special URL that will request WEBrick to die. It can be a command run in a different shell, or, as I said, a special URL. Anyone? Tom Harris Cisco Systems -- Posted via http://www.ruby-forum.com/.

We don't see any attachments... Can you post it somewhere, then include a link? As for the SID errors, what are you using for the DNS server? On Thu, Apr 21, 2016 at 8:37 AM, Stefan Fuhrmann < stefan at fuhrmann.homedns.org> wrote: > Hello all, > can someone help? > > Tia > Stefan > > Am Wednesday 20 April 2016, 14:19:42 schrieb Stefan Fuhrmann: > > Hello

Buenas Tengo en un string guardado lo siguiente: > parametros [1] "ntree=10" "ntree=30" "ntree=50" "ntree=100" "ntree=200" Con un bucle for quiero ir metiendolo en el modelo, pero no se muy bien como hacerlo, ya que con deparse no me funciona, con get tampoco (obvio, no es un objeto), y no se muy bien como hacerlo de manera dinamica

Hola miembros de la lista, Estoy buscando una manera de elaborar tareas o examenes interactivos para mis clases de estadística con R. He visto 2 paquetes muy interesantes que son, learnr y gradethis, pero todavía no logro entender completamente su dinámica. Por lo que entiendo, en gradethis si el estudiante se equivoca tiene la posibilidad de reintentar hasta dar con la solución, lo cual no lo

Hi Sacha, On second thought, perhaps this is more the direction that you want ... X2 = cbind(X_train,y_train) colnames(X2)[3] = "y" regr2<-randomForest(y~x1+x2, data=X2,maxnodes=10, ntree=10) regr regr2 #Make prediction predictions= predict(regr, X_test) predictions2= predict(regr2, X_test) HTH, Eric On Tue, May 9, 2023 at 6:40?AM Eric Berger <ericjberger at gmail.com>

Hi, all I am trying to use the label_wrap_gen function in this website. https://github.com/hadley/ggplot2/wiki/labeller I tried to make a long name like this Light and heavy good vehicles (diesel) -\nGVX f2 = facet_grid(vehicle ~ ., labeller=label_wrap_gen(width=15)) eventually, I got something like this in my label... *Light and heavy good vehicles (diesel) - GVX* I suppose the

Hi, I would like to use a random Forest model to get an idea about which variables from a dataset may have some prognostic significance in a smallish study. The default for the number of trees seems to be 500. I tried changing the default to ntree=2000 or ntree=200 and the results appear identical. Have changed mtry from mtry=5 to mtry=6 successfully. Have seen same problem on both a Windows

Muchas gracias Emilio. Sí, yo cometí un error, veo exams puede usar Rmarkdown también. Manuel El dom., 29 mar. 2020 a las 9:11, Emilio L. Cano (<emilopezcano en gmail.com>) escribió: > Manuel, > > No conozco learnr ni gradethis, pero simplemente como apunte decirte que > con exams puedes utilizar Rmarkdown. > > Un saludo, > > Emilio L. Cano >

I am having trouble with the rfImpute function in the randomForest package. Here is a sample... clunk.roughfix<-na.roughfix(clunk) > > clunk.impute<-rfImpute(CONVERT~.,data=clunk) ntree OOB 1 2 300: 26.80% 3.83% 85.37% ntree OOB 1 2 300: 18.56% 5.74% 51.22% Error in randomForest.default(xf, y, ntree = ntree, ..., do.trace = ntree, : NA not

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I tried rfImpute (randomForest) and as far as I understood should it replace NA`s using a proximity matrix: > set.seed(100000) > Subset5Imputed<-rfImpute(Sex~., data=Subset5) ntree OOB 1 2 300: 11.78% 12.36% 11.21% ntree OOB 1 2 300: 12.07% 12.64%

Hi, I'm using package "caret" to rank predictors using random forest model and draw predictors importance plot. I used below commands: rf.fit<-randomForest(x,y,ntree=500,importance=TRUE) ## "x" is matrix whose columns are predictors, "y" is a binary resonse vector ## Then I got the ranked predictors by ranking

Dear Researches, I am using RF (in regression way) for analize several metrics extract from image. I am tuning RF setting a loop using different range of mtry, tree and nodesize using the lower value of MSE-OOB mtry from 1 to 5 nodesize from1 to 10 tree from 1 to 500 using this paper as refery Palmer, D. S., O'Boyle, N. M., Glen, R. C., & Mitchell, J. B. O. (2007). Random Forest Models

Hi all, Can some one tell me the difference between the following two formulas? 1. epiG.rf <-randomForest(gamma~.,data=data, na.action = na.fail,ntree = 300,xtest = NULL, ytest = NULL,replace = T, proximity =F) 2.epiG.rf <-randomForest(gamma~.,data=data, na.action = na.fail,ntree = 300,xtest = NULL, ytest = NULL,replace = T, proximity =F) [[alternative HTML version deleted]]

Dear List, I built a package under both Mac and Win 7 (both on R 2.12.0) . One of the functions in the package is set up to print a status message using the code below: if (verbose) if ((i %% 10) == 0 && i < ntree) message( "", i, "out of", ntree, "trees so far...") This works perfectly on the Mac. However, on Win 7 the message is not printed

Hi, is it correct that i need ~ 2GB RAM that it's possible to work with the default setting ntree=500 and a data.frame with 100.000 rows and max. 10 columns for training and testing? P.S. It's possible calculate approximate the memory demand for different settings with RF? Many thanks & regards, Christian

Gracias Carlos y Javier, ntrees es el nº de árboles y treesize sus respectivos tamaños (nº de nodos) ntree: Number of trees to grow. This should not be set to too small ...... treesize: Size of trees (number of nodes) in and ensemble. Puse 1000 árboles (ntree=1000), si, pero la función treesize te da el nº de nodos: treesize(RFfit, terminal=TRUE) me da un vector de 1000 elementos (uno

Dear R-devel, Inspired by Michael Li's talk at JSM, I decided to try rpvm and snow on our two linux boxes. It only took me a couple of hours of screwing around to get it working (sooner if I had RTFM). Our setup is: 2 dual PIII-866 Xeons, one with 2GB RDRAM, the other with 1.28GB RDRAM. The first machine is acting as the NIS/NFS server. both /usr and /home are exported to the second

Dear All, For a data mining project, I am relying heavily on the RandomForest and Party packages. Due to the large size of the data set, I have often memory problems (in particular with the Party package; RandomForest seems to use less memory). I really have two questions at this point 1) Please see how I am using the Party and RandomForest packages. Any comment is welcome and useful.