similar to: randomForest

Hello, I'm trying to find out the optimal number of splits (mtry parameter) for a randomForest classification. The classification is binary and there are 32 explanatory variables (mostly factors with each up to 4 levels but also some numeric variables) and 575 cases. I've seen that although there are only 32 explanatory variables the best classification performance is reached when

Hi there, How to solve the conflicts as to the same object between two packages, for example, like margins in both randomForest and supclust? When both libraries are installed, supclust will complain "margins" defined in randomForest. I can only solve it by re-starting R, which is very inconvenient, any clever way? Thanks, Weiwei -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc.

Hello there, I am working on an extremely unbalanced two class classification problems. I wanna use "classwt" with "down sampling" together. By checking the rfNews() in R, it looks that classwt is not working yet. Then I looked at the software from Salford. I did not find the down sampling option. I am wondering if you have any experience to deal with this problem. Do you

hi, i have another question on tapply: i have a dataset z like this: 5540 389100307391 2600 5541 389100307391 2600 5542 389100307391 2600 5543 389100307391 2600 5544 389100307391 2600 5546 381300302513 NA 5547 387000307470 NA 5548 387000307470 NA 5549 387000307470 NA 5550 387000307470 NA 5551 387000307470 NA 5552 387000307470

Hi, there: I spent some time on this but I think I really cannot figure it out, maybe I missed something here: my data looks like this: > dim(trn3) [1] 7361 209 > dim(val3) [1] 7427 209 > mg.rf2<-randomForest(x=trn3[,1:208], y=trn3[,209], data=trn3, xtest=val3[, 1:208], ytest=val3[,209], importance=T) my test data has 7427 observations but after prediction, > dim(mg.rf2$votes)

Hi, I am trying to make a multi-class classification tree by using rpart. I used MASS package'd data: fgl to test and it works well. However, when I used my small-sampled data as below, the program seems to take forever. I am not sure if it is due to slowness or there is something wrong with my codes or data manipulation. Please be advised ! The data is described as the output from str()

Stock returns and other financial data have often found to be heavy-tailed. Even Cauchy distributions (without even a first absolute moment) have been entertained as models. Your qq function subtracts numbers on the scale of a normal (0,1) distribution from the input data. When the input data are scaled so that they are insignificant compared to 1, say, then you get essentially the

Hi there, I have a statistics question on a classification problem: Suppose I have 1000 binary variables and one binary dependent variable. I want to find a way similar to PCA, in which I can find a couple of combinations of those variables to discriminate best according to the dependent variable. It is not only for dimension reduction, but more important, for finding best way to construct

Dear Listers: I have a question on handling large dataset. I searched R-Search and I hope I can get more information as to my specific case. First, my dataset has 1.7 billion observations and 350 variables, among which, 300 are float and 50 are integers. My system has 8 G memory, 64bit CPU, linux box. (currently, we don't plan to buy more memory). > R.version _ platform

Hi there, I need a network builder and it can change the node size and color; I am not sure if network package in R can do this or not. The other functions I wanted have been found in that package. BTW, if there is another package in R relating to this, please suggest too. Thanks, Weiwei -- Weiwei Shi, Ph.D Research Scientist "Did you always know?" "No, I did not. But I

Hi, there: After I upgraded my R to 2.4.1, it is my first time of trying to use MASS and found the following error message: > install.packages("MASS") --- Please select a CRAN mirror for use in this session --- trying URL 'http://cran.cnr.Berkeley.edu/bin/macosx/universal/contrib/2.4/VR_7.2-33.tgz' Content type 'application/x-gzip' length 995260 bytes opened URL

Hi, I searched the archives and did not find a good solution to that. assume I have 10 sets and I want to have the common character elements of them. how could i do that? -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

Hi, there: I think i need to re-phrase my question since last time I did not get any reply but i think the question is not that hard, probably i did not make the question clear: I want to find cases like 35, 90, 330, 330, 335 from the rest which look like 3, 3, 3, 3.2, 3.3 4, 4.4, 4.5, 4.6, 4.7 .... basically there is one (or more) big 'gap' in the case i seek. thanks, weiwei --

Hi, there: I am wondering if there is a quick way to "reverse" a list like this: t0 <- list(a=1, b=1, c=2, d=1) reverst t0 to t1 > t1 $`1` [1] "a" "b" "d" $`2` [1] "c" thanks. -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

Hi, I have a question on read.table. I have a dataset with 273,000 lines and 195 columns. I used the read.table to load the data into R: trn<-read.table('train1.dat', header=F, sep='|', na.strings='.') I found it takes forever. then I run 1/10 of the data (test) using read.table again. And this time it finished quickly. So, there might be something wrong in my data

Hi, I am wondering how to make a function Fun to make the following work: t0 <- (paste("hgu133a", "ENTREZID", sep="")) xx <- as.list(Fun(t0)) # make it work like xx<-as.list(hgu133aENTREZID) thanks, -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc. "Did you always know?" "No, I did not. But I believed..." ---Matrix III

Hi, I have a dataset which has around 138 variables and 30,000 cases. I am trying to calculate a mahalanobis distance matrix for them and my procedure is like this: Suppose my data is stored in mymatrix > S<-cov(mymatrix) # this is fine > D<-sapply(1:nrow(mymatrix), function(i) mahalanobis(mymatrix, mymatrix[i,], S)) Error in solve.default(cov, ...) : system is computationally

Hi, I have a dataset and want to build a generalized linear model on it. Unfortunately, complete.cases(df) returns null, which means I have to find a way to "fill" those missings. One way is following my previous post to use median to replace(or use most freq. of level to replace for catergorical case), but I am wondering if there are other ways, when glm or something like it is

Hi, I have a question on write.table: I have a data.frame called t7 as below: > dim(t7) [1] 14015184 6 > t7[1:5,] uci uce par line graphical.forms stems 1 0 0 0 0 active activ 2 0 0 0 0 policy polici 3 0 0 0 0 wc PC 4 0 0 0 0 eff elf 5 0 0 0 0 icn ICC I want to write the

Hi, I am trying to print out my confusion matrix after having created my random forest. I have put in this command: fit<-randomForest(MMS_ENABLED_HANDSET~.,data=dat,ntree=500,mtry=14, na.action=na.omit,confusion=TRUE) but I can't get it to give me the confusion matrix, anyone know how this works? Thansk! Ruben [[alternative HTML version deleted]]