similar to: need help with nnet

HI, Dear R community, I want to know how to select the optimal decision threshold from the ROC curve? At what threshold will give the highest accuracy? Thanks! -- Sincerely, Changbin -- [[alternative HTML version deleted]]

Hi R-Helpers , am working on nnet package.Multinom() has an option for finding the goodness of fit by giving the AIC value. Does nnet also gives some value to determine the accuracy. If not, can you guide me with some procedure to figure out the accuracy/goodness of fit of nnet model? Thanks in advance. -- View this message in context:

sorry, I forgot my sessionInfo: please see below. -------- Original Message -------- Subject: puzzled with plotmath Date: Thu, 20 Jan 2011 12:48:18 +0100 From: Claudia Beleites <cbeleites at units.it> To: R Help <r-help at r-project.org> Dear all, I'm puzzled with matrix indices in plotmath. I'm plotting matrix elements: Z [i, i], and I'd like to put that as label.

Dear list, I'm stuck with looking for a function of the *apply family, which I suppose exists already ? just I can't find it: What I'm looking for is somewhere between sweep and mapply that does a calculation vectorized over a matrix and a vector: It should work complementary to sweep: for each row of the matrix, a different value of the vector should be handed over. Close to

somfunc<- function (file) { aa_som<-scale(file) final.som<-som(data=aa_som, rlen=10000, grid=somgrid(5,4, "hexagonal")) pdf(file="/home/cdu/changbin/file.pdf") #output graphic file. plot(final.som, main="Unsupervised SOM") dev.off() } I have many different files, if I want output pdf file with the same name as for each dataset I feed to the function

Dear R users, Here is my problem: I have an array with at least four dimensions: > dim(myArray) [1] 20 17 3 6 I'd like to apply a function to each occurrence of the matrix (3x6) defined by the last two dimensions. This interpolation function always return a matrix of the same dimensions as its argument: > interpSecteurs.f(myArray[1, 1, , ]) secteur rotation 1 2 3

I'm attempting to sort a 3 dimensional array that looks like this > x , , 1 [,1] [,2] [1,] 9 9 [2,] 7 9 , , 2 [,1] [,2] [1,] 6 5 [2,] 4 6 , , 3 [,1] [,2] [1,] 2 1 [2,] 3 2 Such that it ends up like this .... > y , , 1 [,1] [,2] [1,] 2 1 [2,] 3 2 , , 2 [,1] [,2] [1,] 6 5 [2,] 4 6 , , 3 [,1] [,2]

Dear Group, I am looking for ways to use R and Matlab. Doing the data transformations in R and using the data in Matlab to analyze with some pre-defined scripts. Any good ways to transfer the data into matlab in its most recent version? I tried using R.matlab but the writeMat output is not readable by Matlab. I just need to output a data.frame and read it as is into matlab where I can do any

Dear all, I work with (vibrational) spectra: some kind of intensity (I) over frequency (nu), wavelength or the like. I want to do fourier transform for interpolation, smoothing, etc. My problem is that the spectra are often irregularly spaced in nu: the difference between 2 neighbouring nu varies across the spectrum, and data points may be missing. Searching for discrete fourier transform

> head(en.id.pr) valid.gene_id b.pred rf.pred svm.pred 1521 2500151211 0 0 0 366 639679745 0 0 0 1965 2502081603 1 1 1 1420 644148030 1 1 1 1565 2500626489 1 1 1 1816 2501711016 1 1 1 > p.pred <- data.frame(en.id.pr, sum=apply(en.id.pr[,2:4], 1, sum)) #

Dear List, I'm struggling with the signature writing cbind/rbind functions for a S4 class. First of all, I'm very happy that it is now possible to dispatch on ... I follow the example for "paste" in ?dotMethods, which works as far as this: ### start example setClass ("cbtest", representation = representation (data = "data.frame"),

Hi, I have the following question about creating data frames. I want to create a data frame with 2 components: a vector and a matrix. Let me use a simple example: y <- rnorm(10) x <- matrix(rnorm(150), nrow=10) Now if I do dd <- data.frame(x=x, y=y) I get a data frame with 16 colums, but if, according to the documentation, I do dd <- data.frame(x=I(x), y=y) then str(dd)

svm.fit<-svm(as.factor(out) ~ ., data=all_h, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) # model fitting svm.pred<-predict(svm.fit, hh, decision.values = TRUE, probability = TRUE) # find the probability, but can not find. attr(svm.pred, "probabilities") > attr(svm.pred, "probabilities") 1 0 1 0 0 2 0

HI, Dear Greg and R community, I have one question about the output of gbm package. the output of Boosting should be f(x), from it , how to calculate the probability for each observations in data set? SInce it is stochastic, how can guarantee that each observation in training data are selected at least once? IF SOME obs are not selected, how to calculate the training error? Thanks? --

Dear R community, I have one function, it works for small data set, but does not work on large data set, can anyone help me with this? > #creat new variable by dividing each aa dimer by total_length. > imper<-function(x, file) { + round(x/file$length, 5) + } > dim(test) [1] 999 2402 > test[varname[2:2401]]<-

Dear all, I just noticed, that prompt () looses backticks that protect default arguments: f <- function (FUN = `*`) {} cat (prompt (f, NA)$usage) yields: \usage{ f(FUN = *) } %- maybe also 'usage' for other objects documented here. without the backticks, which is of course found by R CMD check as syntax error. While this is easily fixed if the .Rd is further edited manually, I

Dear all, I have run into a problem when running some code implemented in the Bioconductor panp-package (applied to my own expression data), whereby gene expression values of known true negative probesets (x) are interpolated onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after updating

Dear List, a second, more general, question concerning S4 classes. I have a bunch of functions/methods for my class. At the moment I have them as methods, because they work on objects of my S4 class and therefore "belong" to that class. On the other hand, it is comparably unlikely that someone else wants the same kind of method. And package.skeleton () produces the

Dear R-Developers, could 'sample' gain a ... argument? As a convenience function, I added a sample Method to my hyperSpec class. This function however has a flag indicating whether the results should be returned directly as a hyperSpec object or rather as indices that give a random sample. For the moment, I use SetGeneric to add the dots argument, but this of course gives a warning

Dear all, I have trouble with R-beta sweaving files that include definitions with \SweaveInput in combination with keep.source = TRUE Symptom: SInput is taken from too far down the input file (the shift is the number of lines of the included file). Is that known? Searching didn't turn up anything, yet I think there are more people than just me using keep.source. Example: $