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In my disk C:/ have a a.csv file, I want to read it to R, importantly, when I use x=read.csv("C:/a.csv") ,the x format is data.frame, I want to it to become matrix format, how can I do it ? thank you! -- View this message in context: http://old.nabble.com/how-can-I-convert-.csv-format-to-matrix----tp26156643p26156643.html Sent from the R help mailing list archive at Nabble.com.

I want to get the plot like this, http://n4.nabble.com/file/n1839303/%25E9%25A2%2591%25E7%258E%2587%25E5%2588%2586%25E5%25B8%2583%25E5%259B%25BE%25E6%25A0%2587%25E5%2587%2586.jpg %E9%A2%91%E7%8E%87%E5%88%86%E5%B8%83%E5%9B%BE%E6%A0%87%E5%87%86.jpg not this, http://n4.nabble.com/file/n1839303/R.jpg R.jpg and the data here, thank you! http://n4.nabble.com/file/n1839303/y1.txt y1.txt can R

e.g. a= a b c d e 1 1 1 3 1 1 2 1 2 3 4 5 3 1 3 3 8 3 4 1 4 3 3 5 5 1 1 3 1 1 I want to delete colume a and colume c, because they have the same values in every row, then ,I want to get this data.frame . b= b d e 1 1 1 1 2 2 4 5 3 3 8 3 4 4 3 5 5 1 1 1 the following is my code but it's wrong. rm(list=ls()) a=c(1,1,1,1,1); b=c(1,2,3,4,1); c=c(3,3,3,3,3);

my programe is below: a=c(1,2,1,1,1); b=c(1,2,3,4,1); c=c(3,4,3,3,3); d=c(1,2,3,5,1); e=c(1,5,3,5,1) data.f=data.frame(a,b,c,d,e) origin.data<-data.f cor.matrix<-cor(origin.data) origin.cor<-cor.matrix m<-0 for(i in 1:(cor.matrix[1]-1)) { for(j in (i+1):(cor.matrix[2])) { if (cor.matrix[i,j]>=0.95) { data.f<-data.f[,-i]; i<-i+1 }

Dear all, My double for loop as follows, but it is little efficient, I hope all friends can give me a "vectorized" program to replace my code. thanks x: is a matrix 202*263, that is 202 samples, and 263 independent variables num.compd<-nrow(x); # number of compounds diss.all<-0 for( i in 1:num.compd) for (j in 1:num.compd) if (i!=j) { S1<-sum(x[i,]*x[j,])

I want to split my whole dateset to training set and test set, building model in training set, and validate model using test set. Now, How can I split my dataset to them reasonally. Please give me a hand, It is better to give me some R code. and I see some ways like using SOM to project whole independents to 2-dimensions and find some to be training set and others are test set. like below. I

This topic refer to independent variables reduction, as we know ,a lot of method can do with it,however, for pre-processing independent varibles, a method like the sentence below can reduce many variable, How can I understand it? what is significant correlation at 5% level, what is the criterion? P value?or what? "Independent variables whose correlation with the response variable was not

http://r.789695.n4.nabble.com/file/n3060425/fig_1.png fig. 1 http://r.789695.n4.nabble.com/file/n3060425/fig_2.png fig. 2 I want to the picture like the above one, the origin crossover together, while the following picture can be obtained by default and the origin is detached, but throgut pulling the window, I can get the one like fig_1. Now, I want to know how to use the code to obtain

hello, my problem is like this: now after processing the varibles, the remaining 160 varibles(independent) and a dependent y. when I used PLS method, with 10 components, the good r2 can be obtained. but I donot know how can I express my equation with the less varibles and the y. It is better to use less indepent varibles. that is how can I select my indepent varibles. Maybe GA is good

now I am learining random forest and using random forest package, I can get the OOB error rates, and test set rate, now I want to get the training set error rate, how can I do? pgp.rf<-randomForest(x.tr,y.tr,x.ts,y.ts,ntree=1e3,keep.forest=FALSE,do.trace=1e2) using the code can get oob and test set error rate, if I replace x.ts and y.ts with x.tr and y.tr,respectively, is the error rate

Usage data(gasoline) Format A data frame with 60 observations on the following 2 variables. octane a numeric vector. The octane number. NIR a matrix with 401 columns. The NIR spectrum and I see the gasoline data to see below NIR.1686 nm NIR.1688 nm NIR.1690 nm NIR.1692 nm NIR.1694 nm NIR.1696 nm NIR.1698 nm NIR.1700 nm 1 1.242645 1.250789 1.246626 1.250985 1.264189 1.244678 1.245913

I am learning the package "caret", after I do the "rfe" function, I get the error ,as follows: Error in `[.data.frame`(x, , retained, drop = FALSE) : undefined columns 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

Hi?all friends, Please help me understand this sentence below: ?From this set, 858 columns not significantly correlated with the response variable TBG at the 5% level were removed, leaving a set of 390 columns.? and ? the F-test's value for the one-parameter correlation with the descriptor is below 1.0? is equal?? I want to perform this above sentence with R, how can I do? I just try

rm(list=ls()) yx.df<-read.csv("c:/MK-2-72.csv",sep=',',header=T,dec='.') dim(yx.df) #get X matrix y<-yx.df[,1] x<-yx.df[,2:643] #conver to matrix mat<-as.matrix(x) #get row number rownum<-nrow(mat) #remove the constant parameters mat1<-mat[,apply(mat,2,function(.col)!(all(.col[1]==.col[2:rownum])))] dim(yx.df) dim(mat1) #remove columns with numbers of

http://r.789695.n4.nabble.com/file/n3031344/RSV.Rdata RSV.Rdata I want to split my dataset to training set and test set using kennard-stone(KS) algorithm, it is lucky there is R packages soil.spec to implement it. but when I used it to my dataset, it does not work, who can help me, how reasons is it, below, it is my code, and my data in the attachment.

...???4. rdcomclient issue - member not found > when using borders > ? ? ? (Jason Baucom) > ???5. Re: If else statements (Matthew > Dowle) > ???6. Re: Problem installing package (David > Winsemius) > ???7. caret package, how can I deal with > RFE+SVM wrong message? > ? ? ? (bbslover) > ???8. information module Wilks' lambda > criterion (Catherine ENG) > ???9. Transform data set (Thomas Jensen) > ? 10. R-installation regarding. (fredrick devadoss) > ? 11. Re: estimation of parameters with grofit > (alexander russell) > ? 12. Re: Embed R code in C++ (man...

...ist at r-help-owner@r-project.org When replying, please edit your Subject line so it is more specific than "Re: Contents of R-help digest..." Today's Topics: 1. 3D Binning (vioravis) 2. help! complete the reviewer's suggest: carry out GA+GP (gaussian process)! (bbslover) 3. nlminb doesn't converge and produce a warning (kamel gaanoun) 4. Loop and store results (Sam) 5. Re: auc function (Petr Savicky) 6. stochastic models for population growth (Vassily Shvets) 7. Re: Loop and store results (Henrique Dallazuanna) 8. Function comparable to cutpt.coxph...

Hello, all experts, My major is computer-aied drug design ( main QSAR). Now, my paper need be reviesed, and one reviewer ask me do genetic algorithm coupled with gaussian process method (GA+GP). my data: training set: 191*106 test set: 73*106 here, I need use GA+GP to do variable selection when building the model. In R, there are not GA package like in matlab

Hello, I am learning caret package, and I want to use the RFE to reduce the feature. I want to use RFE coupled Random Forest (RFE+FR) to complete this task. As we know, there are a number of pre-defined sets of functions, like random Forest(rfFuncs), however,I want to tune the parameters (mtr) when RFE, and then I write code below, but there is something wrong message, How can I deal with it?