similar to: outliers using Random Forest

Subject: Eliminate repeated components from a vector X-Mailer: VM 7.00 under 21.4 (patch 6) "Common Lisp" XEmacs Lucid Reply-To: fjmolina at lbl.gov FCC: /home/f/.xemacs/mail/sent Does anyone know how I can eliminate repeated elements from a vector?

I was wandering if anybody ever tried to compare the classification accuracy of nnet to other (rpart, tree, bagging) models. From what I know, there is no reason to expect a significant difference in classification accuracy between these models, yet in my particular case I get about 10% error rate for tree, rpart and bagging model and 80% error rate for nnet, applied to the same data. Thanks.

Hi, I am currently writing code to input a few thousand files, run them through the Random Forests package, and then output corresponding results. When I use the code below: zz<-textConnection("ex.lm.out", "w") sink(zz)

Hello, I am using the dunn metric, but something is wrong and I dont understand what or what that this error mean. Please can you help me with this? The instructions are: #Indice de Dunn disbupa=dist(bupa[,1:6]) a=hclust(disbupa) cluster.stats(disbupa,a,bupa[,7])$dunn And the error is: Error in max(clustering) : invalid 'type' (list) of argument thank you so much. Ana Maria

Dear all, I am a total beginner in R, so sorry if this is the wrong place. I am using R 2.10.1 on a Mac (Mac OS 10.6.2). I have this small dataset : growth sugar 75 C 72 C 73 C 61 F 67 F 64 F 62 S 63 S I have no problem reading the table, or getting the summary, but if I try boxplot(growth~sugar, ylab="growth", xlab="sugar", data=Dataset), I have the following error :

hello all, i'm trying to use QPmat, from the popbio package. it appears to be based on solve.QP and is intended for making a population projection matrix. QPmat asks for: nout, A time series of population vectors and C, C constraint matrix, (with two more vectors, b and nonzero). i believe the relevant code from QPmat is: function (nout, C, b, nonzero) { if (!"quadprog" %in%

R community, As you may know, R's iconv doesn't work well converting to and from encodings that allow embedded nulls. For example > iconv("foo", to="UTF-16") Error in iconv("foo", to = "UTF-16") : embedded nul in string: '\xff\xfef\0o\0o\0' However, I don't believe embedded nulls are at issue here, but rather that R's iconv

Hi, I'm a new user of R. My background is Electrical Engineering, so please bear with me if this is a silly question. I'm trying to assess whether the results of an experiment satisfy the hypothesis of homoscedasticity (my ultimate goal is to use ANOVA). The result of the experiment is mean delay (dT), which depends on three factors, topology, drift, and lambda. The first two factors are

Hi, I would like to find some methods about feature selection, but I only know the package "randomForest" after searching for a while. Could you recommend some other packages of feature selection? Thank you very much. Sincerely yours, Chad Yang. ==========================================================

Hi all, While compiling R to RISC-V64 architecture and debugging in R's C source codes, I think I have found a small bug. Can anyone please verify whether it is a real bug? The possible bug lies in the file `R-4.2.2/src/library/stats/src/approx.c` in function `R_approxfun` around line 148: #ifdef DEBUG_approx REprintf("R_approxfun(x,y, nxy = %.0f, .., nout = %.0f, method = %d,

Friends, Is there a Partial Least Squares package implemented in R? Thanks, Lana [[alternative HTML version deleted]]

Dear all, you can find below my solution for sliding a window. Please find below the code for the two alternatives and the benchmarks.     install.packages('caTools') require(caTools) do_sliding_for_a_window_duty_cycle <- function(DataToAnalyse,  windowSize) {   data<-DataToAnalyse   out <- numeric()   elements<- numeric()   if (length(data[,1]) >= windowSize){       for

Hi all, I originally posted this to the bioconductor group, but maybe it's better suited to the r-help... I'm using som() to partition samples of gene expression data into clusters. The point is to classify control vs. experimental cases (sample clustering). The original matrix was 22283 x 8. The 8 samples have 4 controls and 4 experimentals. I transposed the matrix so that its dim

Hi, I'd like to add, say, the sample size for every group in a bwplot as a parenthetical annotation to the axis. Here's a sketch: --8<---------------cut here---------------start------------->8--- require(Hmisc) age <- sample(1:100, 1000, replace = TRUE) sex <- gl(2, 8, 1000, c("Male", "Female")) grp <- gl(4, 6, 1000, letters[1:4]) bwplot(grp ~ age |

Hello, I was wondering if there is an easy way to authenticate users through ldap, or pam (which uses ldap). In our current setup samba uses tdbsam. I would like users to be authenticated to our existing ldap server (slapd on debian etch). So that if the user has been authenticated successfully (s)he can access the directories as configured in smb.conf (/home/username, /public etc.) with the

> On Sep 14, 2016, at 12:23 PM, Achim Gottinger via samba <samba at lists.samba.org> wrote: > > > > Am 14.09.2016 um 18:23 schrieb Michael A Weber: >> Question though, just for my curiosity: >> >> The encryption algorithms specified after each SPN: I see that aes-256 is listed when I export the user, but not the SPN. Are those expected, or have I done

Hi, this is both a statistical and a R question... what would the best way / test to detect an outlier value among a series of 10 to 30 values ? for instance if we have the following dataset: 10,11,12,15,20,22,25,30,500 I d like to have a way to identify the last data as an outlier (only one direction). One way would be to calculate abs(mean - median) and if elevated (to what extent ?) delete the

On 09.03.2012 15:09, yahoo2 wrote: > Uncompressed FLAC is called WAV. really? ;-) the problem is that there is no standarized way to store metadata in a WAVE file, like with FLAC tags / vorbis comments in flac files.... greets KoS

Hi. I want to do an lmer model but have doubts of what family I should use. My response variable was originally a proportion, however I standarized it for each year of data collection (20 in total). After standarizing it I checked for normality with the Kolmogorov-Smirnov test, and it turns out it is not normal. It ranges from -3 to 4. Since it is no longer a proportion I can't use a

Can any one help me to solve problem in my code? I am actually trying to find the stopping index N. So first I generate random numbers from normals. There is no problem in finding the first stopping index. Now I want to find the second stopping index using obeservation starting from the one after the first stopping index. E.g. If my first stopping index was 5. I want to set 6th observation from