similar to: caret: compare linear models of different degree

I want to use the caret package and found out about the timingSamps obtion to obtain the time which is needed to predict results. But, as soon as I set a value for this option, the whole model generation fails. Check this example: ------------------------- library(caret) tc=trainControl(method='LGOCV', timingSamps=10) tcWithout=trainControl(method='LGOCV')

Hy, I got the following problem when trying to build a rpart model and using everything but LOOCV. Originally, I wanted to used k-fold partitioning, but every partitioning except LOOCV throws the following warning: ---- Warning message: In nominalTrainWorkflow(dat = trainData, info = trainInfo, method = method, : There were missing values in resampled performance measures. ----- Below are some

Hi all I am using the caret package and having difficulty in obtaining the results using regression, I used the glmnet to model and trying to get the coefficients and the model parameters I am trying to use the extractPrediction to obtain a confusion matrix and it seems to be giving me errors. x<-read.csv("x.csv", header=TRUE); y<-read.csv("y.csv", header=TRUE);

Dear R committee: I am Renzhi, Ph.D student in computer science in the University of Missouri. I have one question for you. I try to install R in the linux server, but I don't have the root permission, is there any way to install the R locally? Thank you very much for helping me. Renzhi Cao Graduate Research Assistant Department of Computer Science University of

Hi list, I´m working on a predictive modeling task using the caret package. I found the best model parameters using the train() and trainControl() command. Now I want to evaluate my model and make predictions on a test dataset. I tried to follow the instructions in the manual and the vignettes but unfortunately I´m getting an error message I can`t figure out. Here is my code: rfControl <-

Hi All, 3.4.0 and 3.3.2 releases of GlusterFS are now available. GlusterFS 3.4.0 can be downloaded from [1] and release notes are available at [2]. Upgrade instructions can be found at [3]. If you would like to propose bug fix candidates or minor features for inclusion in 3.4.1, please add them at [4]. 3.3.2 packages can be downloaded from [5]. A big note of thanks to everyone who helped in

Hi I have a problem accessing an array field in a Postgresql database. Here is the table definition. View "neil.flashing_codes" Column | Type | Modifiers -------------+-----------------------+----------- code | character varying(10) | description | text | folds | integer[] | View definition: SELECT

I am trying to run an ancova and am having trouble setting it up properly. I have nearly 10,000 measurements of fish length, girth and stage of sexual development. I am suspicious that the stage of development is affecting the length (as they get full of eggs they get more round and are more difficult to measure and measure shorter). My data looks somethign like this: Length girth stage 40 50

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi Everyone, I often use the 'safe prediction' feature available through glm(). Now, I'm at a situation where I must use biglm:::bigglm. ## begin example library(splines) library(biglm) ff <- log(Volume)~ns(log(Girth), df=5) fit.glm <- glm(ff, data=trees) fit.biglm <- bigglm(ff, data=trees) predict(fit.glm, newdata=data.frame(Girth=2:5)) ## -1.3161465 -0.2975659

Yes, I am a newbie at R, but it is not the complex commands in R that have me baffled, but simple data commands. For example, why does something like: > plot(Girth ~ Height) *not* work after a command that allegedly loads the data: > data(trees) with the error message: Error in eval(expr, envir, enclos) : Object "Girth" not found but does work after the command: >

In a rather simple regression, I?d like to ask the question, for high trees, whether it makes a difference (for volume) whether a three is thick. If my interpretation is correct, for low trees, i.e. for which trees$isHigh == FALSE, the answer is yes. The problem is how to "merge" the standard errors. Code follows. data(trees) trees$isHigh <- trees$Height > 76 trees$isThick

The "earth" package is now available on CRAN. Earth builds models using Friedman's MARS. Earth's principal advantages over the existing function mda::mars are that it is much faster and provides plotting and printing methods. The general purpose model plotting function "plotmo" may also be useful to people who are not interested in earth itself. Example: > a

The "earth" package is now available on CRAN. Earth builds models using Friedman's MARS. Earth's principal advantages over the existing function mda::mars are that it is much faster and provides plotting and printing methods. The general purpose model plotting function "plotmo" may also be useful to people who are not interested in earth itself. Example: > a

Hi all, first of all, I'm not an expert on R, I'm still learning, so sorry if this is a stupid question... I have a large dataset that is to big for my computer memory, and I found quite useful the package biglm. Now everything is working perfectly. But if I want the residuals, how I can do it? Let's say that we are running the example: > data(trees)>

Hi all, I'm an R newbie, I did this script to create a scatterplot using the "tree" matrix from "datasets" package: library('datasets') with(trees, { plot(Height, Volume, pch=3, xlab="Height", ylab="Volume") symbols(Height, Volume, circles=Girth/12, fg="grey", inches=FALSE, add=FALSE) } ) I'd like to use the column Named

I tried to run the following example from section 4.1.4 of the "Scatterplot3d - an R package for Visualizing Multivariate Data" vignette and got an error on the part that plots the regression plane: > library(scatterplot3d) > data(trees) > s3d <- scatterplot3d(trees, type = "h", color = "blue", + angle = 55, scale.y = 0.7, pch = 16, main = "Adding

Dear R helpers, I have a 3D scatter plot that I have generated from scatterplot3d (which looks great- thanks!) and I can see that the points in my graph fall in a plane. Following the example 5 from 3D scatter plot (below) I have fitted a regression plane. Now what I would like to do is a rotation so that my new co-ordinate system is about the fitted plane (by finding the normal to the plane

I am seeing this crashing happening, I am working on the self healing errors as well, not sure if the two are related. I would appreciate any direction on trying to resolve the issue, I have clients dropping connection daily. [2013-10-26 15:35:46.935903] E [afr-self-heal-common.c:2160:afr_self_heal_completion_cbk] 0-ENTV04EP-replicate-9: background meta-data self-heal failed on / [2013-10-26

Hi All. I'd like to programm a 4 dimensional chart in R. Acctually I wanted to solve that problem in Excel cause I had the data there. Here is a link of my actual problem description (there are some chart pictures as well).... http://www.mrexcel.com/board2/viewtopic.php?t=187336&highlight=stacked+column because I still couldn't solve that problem I came to R. The chart should be