search for: lmfuncs

Hi developers, After some investigation I have found there can be large discrepancies in the same object being saved as an external "xx.RData" file. The immediate repercussion of this is the possible increased size of your .RData workspace for no apparent reason. The function and its three scenarios below highlight these discrepancies. Note that the object being returned is exactly

...umns selected In addition: Warning message: In predict.lm(object, x) : prediction from a rank-deficient fit may be misleading I try to that manual example, that is good, my data is wrong. I do not know what reanson? my code is : subsets<-c(1:5,10,15,20,25) ctrl<-rfeControl(functions=lmFuncs, method = "cv", verbose=FALSE,returnResamp="final") lmProfile<-rfe(trainDescr,trainY,sizes=subsets,rfeControl=ctrl) before it, I have do some pre-process and my data is in the attachment. Please help me. thank you! kevin http://n4.nabble.com/file/n996068/t...

...h 3 levels. x <- chlDescr y <- chl #crate dummy variable levels(x$State) <- c("AL","GA","FL") dummy <- model.matrix(~State,x) z <- cbind(dummy, x) #remove State category variable w <- z[,c(-4)] subsets <- c(2:8) ctrl<- rfeControl(functions = lmFuncs, method="cv", verbose=FALSE, returnResamp = "final") lmProfile <- rfe(w, y, sizes = subsets, rfeControl = ctrl) Returns: Error in `[.data.frame`(x, , retained, drop = FALSE) : undefined columns selected In addition: Warning message: In predict.lm(object, x) : predictio...

On a Unix machine I ran caret::rfe using the multicore package, and I saved the resulting object using save(lm2, file = "lm2.RData"). [Reproducible example below.] When I try to load("lm2.RData") on my Windows laptop, I get Error in loadNamespace(name) : there is no package called 'multicore' I completely understand the error and I would like to ignore it and