similar to: SVM regression

Dear list, I have some difficulty in manipulating list elements. More specifically, I am performing svm regression and have a list of lists, called pred.svm. The elements of the second list are 3D arrays. Thus I have pred.svm[[i]][[j]], with 1<=i<=5 and 1<=j<=20. I want to take the sum of the elements a specific array dimension across all j, for one i. Mathematically speaking, I want

Hi all, I am trying to draw a Kaplan-Meier curve and I found online that Kaplan - Meier estimates are computed with a function called km in the event package. Is there an update for that because when I choose to download packages in R,. there is no package called event, even though I have selected all the repositories. Thanks in advance, Eleni [[alternative HTML version deleted]]

Hi This is a question regarding classification performance using different methods. So far I've tried NaiveBayes (klaR package), svm (e1071) package and randomForest (randomForest). What has puzzled me is that randomForest seems to perform far better (32% classification error) than svm and NaiveBayes, which have similar classification errors (45%, 48% respectively). A similar difference in

Hello list, I am trying to apply the paired t.test between diseased and not diseased patients to identify genes that are more expressed in the one situation under the other. In order to retrieve the genes that are more expressed in the positive disease state I do: p.values<-c() for(i in 1:length(Significant[,1])){ p.values[i]<-try(t.test(positive[i,],negative[i,],alternative

Hello all! I am performingsome clustering analysis on microarray data using agnes{cluster} and I have created my own dissimilarity matrix according to a distance measure different from "euclidean" or "manhattan" etc. My question is, if I choose for example method="complete", how are the distances between the elements calculated? Are they taken form the dissimilarity

Hi all! I am new to R and I would like to ask you the following question:How can I substitute the NA values with 0 in a data frame? I cannot find a command to check if a value is NA... Thank you very much! Eleni

Dear list, I am trying to perform a significance analysis of a microarray experiment with survival data using the {samr} package. I have a matrix containing my data which has 17816 rows corresponding to genes, and 286 columns corresponding to samples. The name of this matrix is data.matrix2. Some of the first values of this matrix are: data.matrix2[1:3,1:5] GSM36777 GSM36778 GSM36779

Hi all, I am trying to install the package "GEOquery" in unix. I have downloaded the standard version of R and this package is not contained in the default. I know that I can select repositories under windows but I don't know how to do it in unix. Does anyone have any idea on this? Thank you in advance, Eleni [[alternative HTML version deleted]]

Hi list! I have recently tried to take my office work home, meaning that I tried to transfer my "... .RData" workspace from my PC on my laptop. The office PC runs on Windows XP and my laptop runs on Windows Vista. I have saved the workspace at the office PC and kept it in a usb drive. When I tried to open it on my laptop I got an error: "Fatal Error: Unable to restore saved data in

Dear list, I have a couple of questions concerning ridge regression. I am using the lm.ridge(...) function in order to fit a model to my microarray data. Thus *model=lm.ridge(...)* I retrieve some coefficients and some scales for each gene. First of all, I would like to ask: the real coefficients of the model are not included in the first argument of the output but in the result of coef(model),

Hello R users, I am trying to run a cox model for the prediction of relapse of 80 cancer tumors, taking into account the expression of 17000 genes. The data are large and I retrieve an error: "Cannot allocate vector of 2.4 Mb". I increase the memory.limit to 4000 (which is the largest supported by my computer) but I still retrieve the error because of other big variables that I have in

Hi I am Aadhithya I am trying to write a code to classify microarray data (AML and ALL) using SVM in R my code goes like this : library(e1071) train<-read.table("Z:/Documents/train.txt",header=T); test<-read.table("Z:/Documents/test.txt",header=T); cl <- c(c(rep("ALL",10), rep("AML",10))); model<- svm(train,cl); pred <-

Hello all, I have the following problem. I want to insert blank rows in an data frame so as to make it comparable with another data frame with more rows. How can I insert these rows? If this is not solvable, then, alternatively, is it easy to delete rows from a data frame? Thanks for helping, Eleni [[alternative HTML version deleted]]

Hello R community, I am processing raw Affymetrix CEL files and I am using the Michigan custom CDF library hgu133plus2hsentrezgprobe. I have been looking for documentation on the function that it contains...I am specifically interested in converting probe names to gene symbols. Does anybody know where I can find it? Thank a lot! Eleni [[alternative HTML version deleted]]

Dear all, I executed svm calculation using e1071 library with a microarray data (http://www.iu.a.u-tokyo.ac.jp/~kadota/R/data_Singh_RMA_3274.txt). Then, I shuffled the data samples and executed svm calculation again. The results of 2 calculation were different (in SV, coefs and weights). I attached the script below. Could please tell me why this happens? If possible please tell me how to make

Hello everyone, I wanted to know if it was possible to change the color of certain leaves in a hclust object in order to make my graph more readable. I know I can color certain groups but I would like to enter a vector telling the plot function which leaves to color in which color. Thanks in advance, Eleni [[alternative HTML version deleted]]

Dear list, I have been searching for a week to fit a simple linear model to my data. I have looked into the previous posts but I haven't found anything relevant to my problem. I guess it is something simple...I just cannot see it. I have the following data frame, named "data", which is a subset of a microarray experiment. The columns are the samples and the rows are the probes. I

Dear list, I am having a set of human oligo ids (H200006022 H200002025 H300004703 H200000442 H200005719 H300018350) which I want to map to Ensembl or RefSeq. I am sure R has a function to do that. I downloaded the {oligo} package and tried to use the probeNames function. Although the factor of ologo ids is an object (as the argument to probeNames should be) I retrieve the following error:

Hi, I have a question about the parameter C (cost) in svm function in e1071. I thought larger C is prone to overfitting than smaller C, and hence leads to more support vectors. However, using the Wisconsin breast cancer example on the link: http://planatscher.net/svmtut/svmtut.html I found that the largest cost have fewest support vectors, which is contrary to what I think. please see the scripts

I run the following code, all other is ok, but plot(m.svm,p5.new,As~Cur) is not ok Anyone know why? install.packages("e1071") library(e1071) library(MASS) p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") p5.new<-subset(p5,select=-Ms) p5.new$Y<-factor(p5.new$Y) levels(p5.new$Y) <- list(Out=c(1), In=c(0)) attach(p5.new)