similar to: change the for loops with lapply

HI, Dear R community, I am writing the following function to create one data set(*tree.pred*) and one vector(*valid.out*) from loops. Later, I want to use the data set from this loop to plot curves. I have tried return, list, but I can not use the *tree.pred* data and *valid.out* vector. auc.tree<- function(msplit,mbucket) { * tree.pred<-data.frame()

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]]<-

> fit.dimer <- rpart(as.factor(out) ~ ., method="class", data=p_df) > > fit.dimer$frame[, "var"] [1] NE WC <leaf> TA <leaf> <leaf> WG WD WW WC [11] <leaf> <leaf> <leaf> CT <leaf> FC <leaf> YG QT <leaf> [21] <leaf> <leaf> NW DP DY <leaf> SK

HI, Dear R community, Last friday, I used the codes, it works, but today, it does not run? > fit.dimer <- rpart(outcome ~., method="class", data=p.df) Error in `[.data.frame`(frame, predictors) : undefined columns selected DOEs anyone have comments or suggestions? Thanks in advance! -- Sincerely, Changbin -- [[alternative HTML version deleted]]

HI, Dear R community, How to extract the variables actually used in tree construction? I want to extract these variables and combine other variable as my features in next step model building. > printcp(fit.dimer) Classification tree: rpart(formula = outcome ~ ., data = p_df, method = "class") Variables actually used in tree construction: [1] CT DP DY FC NE NW QT SK TA WC WD WG WW

HI, Dear R community, I have a large data set names dd.txt, the columns are: there are 2402 variables. a1, b1, ..z1, a11, b11, ...z11, a111, b111, ..z111.. IF I dont know the relative position of the columns, but I know I need the following variables: var<-c(a1, c1,a11,b11,f111) Can I use read.columns to read the data into R? I have tried the following codes, but it does not work

Dear community, I have one file named ca_boost_feature.txt, Feature selection (Boosting:0.0025,5)! H.2.C C.1.D C.3.R E.0.N C.2.S C.0.G H.3.G log file: ep If I want to use the second line of this file, how to read it into R? varr<-read.table("/home/cdu/operon/carbonic/ca_boost_feature.txt", sep=" ", skip=1, header=F, strip.white=TRUE, nrows=1) Warning message: In

Hi R people. &nbsp; I have a problem. What can I create by using functions the combinations of&nbsp;distances in multiple comparisons tests such as duncan multiple range test? &nbsp; cur=sample(rnorm(15),15,replace=TRUE) varr=factor(c(rep("var1",5),rep("var2",5),rep("var3",5))) dat&lt;-data.frame(cur, varr) lmm&lt;-lm(cur~ varr,data=dat)

Hi All, I have millions of regression lines to fit. So I am looking for the most efficient approach in R. Details: I have a large desing matrix X. The dimension is n by p. Each time when fitting the model, select rows from this matrix X and form a new design matrix, called X_current. There is another binary matrix M, with dim m by n, and each row is a 1*n vector. It helps to determin X_current.

HI, Dear R community, My data set has 2409 variables, the last one is response variable. I have used the nnet after feature selection and works. But this time, I am using nnet to fit a model without feature selection. I got the following error information: > dim(train) [1] 1827 2409 nnet.fit<-nnet(as.factor(out) ~ ., data=train, size=3, rang=0.3, decay=5e-4, maxit=500) # model

HI, Dear R-community, I AM using the following codes to grow tree and plot tree: # Classification Tree with rpart library(rpart) pdf(file="/home/cdu/changbin/dimer_tree.pdf") # grow tree fit.dimer <- rpart(outcome ~ ., method="class", data=p.dimer[,2:402]) plotcp(fit.dimer) # visualize cross-validation results # plot tree plot(fit.dimer, uniform=TRUE,

I'm trying to create a new column in my data.frame where subjects are categorized depending on values on four other columns. In any other case I would just nest a few ifelse statements, however, in this case i have 4*6*2*3=144 combinations and i get weird 'context overflow' errors. So I wonder if there is a more efficient way of doing this. For illustrational purposes, let's say

Hello, I?m hoping you have a few minutes to help out someone very new to R. I?ve done some searching, but cannot find this particular issue. I have survey data from two different time periods (years). Both years are stratified samples and have the same variables (and variable names), but are different people in the community answering in the different years. Everything loads into the survey

On Wed, Apr 6, 2016 at 11:16 AM, Peter Collingbourne <peter at pcc.me.uk> wrote: > On Wed, Apr 6, 2016 at 10:49 AM, Teresa Johnson <tejohnson at google.com> > wrote: > >> >> >> On Wed, Apr 6, 2016 at 10:46 AM, Peter Collingbourne <peter at pcc.me.uk> >> wrote: >> >>> I suspect that the right way to do promotion/renaming of this

Dear all, When porting my package to WinXP I have the following problem: I need to create an environment variable "MYVAR=c:\mypath" which I have saved in the control panel "System->My Computer" (under the `Advanced' tab). I have two files which need to access MYVAR: config.win, Makefile.win While "config.win" does recognize MYVAR correctly,

I still wonder if this would be an issue in _standard_ (not thin) LTO? This test seems to be OK on my (slightly modified) standard LTO flow, but I do wonder for a more general case. Sergei --- Qualcomm Innovation Center, Inc. is a member of Code Aurora Forum, hosted by The Linux Foundation From: llvm-dev [mailto:llvm-dev-bounces at lists.llvm.org] On Behalf Of Peter Collingbourne

On Wed, Apr 6, 2016 at 10:46 AM, Peter Collingbourne <peter at pcc.me.uk> wrote: > I suspect that the right way to do promotion/renaming of this sort is to > rename at the MC layer just before writing the symbol table to the object > file. > I think that is too late - how would the symbols be distinguished in the LTO case below after the IR is linked but before we renamed the

I encountered an issue with ThinLTO handling of inline assembly, where the inline assembly referenced a constant that was a local variable. The local var was renamed because it was promoted in ThinLTO mode, but the inline assembly copy was not renamed and we ended up with an undef at link time. It looks like this is a general problem with inline assembly and LTO. Wondering if it is a known issue.

Hi, I''ve got a problem when using templates in Puppet. In my node declarations, i set (or not) some special variables to activate (or not) some part of my configuration. When i don''t need the configuration part, i don''t declare the variable. I then use something like this in my templates: ... <% if defined? myvar %> ... myvalue = <%= myvar %> ... <%

Hello I haven't found an example on how to compare the value of a string variable with spaces in it, and the While loop below never exits: ========== extensions.conf exten => start,n,Set(MYVAR="Dummy value") exten => start,n,NoOp(${MYVAR}) ;BAD TOO ;exten => start,n,While(!$[${MYVAR} : "Some string"]) exten => start,n,While($[${MYVAR} != "Some