search for: madhurima_b

Hello Everybody, I am trying to perform SAM with the samr package. I am using the following code: sink ("R005") library(siggenes) library(samr) library(nnet) A <- as.matrix(read.table("D:\samrgenes1000.txt")) B <- as.matrix(read.table("D:\genenames1000.txt")) y1 <- c(rep(1,20),rep(2,6)) #there are 20 chips of one kind and 6 of the other kind. datasam =

Hello Everybody, I am running a R script through a perl code from command line. The perl script is like: my $cmd= 'R CMD BATCH D:/try5.R'; system($cmd); I run the perl code from command line. Now I want to pass some command line arguments to the R script. Its like the argv concept of perl. Do I pass the arguments through my $cmd in the perl script? If yes, then how to access that in

Hello All, I am working with samr and nnet packages. I am following the steps given below: 1> I take a input file with signal values for 9506 genes and 36 chips , belonging to two classes. 2> I perform samr analysis on 80% of chip data from both the classes.(selected by random sampling) 3> I then use the data of only the significant genes from this samr analysis to train nnet. 4>

Dear R people, I want to use the tune.nnet function of e1071 package to tune nnet . I am unable to understand the parameters of tune.nnet from the e1071 pdf document. I have performed nnet on a traindata and want to test it for class prediction with a testdata. I want to know the values of size,decay,range etc. parameters for which the prediction of testdata is best. Can anyone please tell me

Dear R people, I am using tune.nnet from e1071 package to tune the parameters for nnet. I am using the following syntax: tuneclass <-c(rep(1,46),rep(2,15)) tunennet <-tune.nnet(x=traindata,y=tuneclass,size=c(50,75,100),decay=c(0,0.005,0.010),MaxNWts = 20000) Here traindata is the training data that I want to tune for nnet which is a matrix with 61 rows(samples) and 200