similar to: sum predictions by hand

hello , I am new user in R . I have datafile (class = data.frame) which has 825 columns with unique column name i want extract 200 selected column from datafile how can I do this? my datafile look like.. Mi RBN RBF nDB nX 3 2.6225979 0.53132756 -0.80599902 -1.4471864 -0.5705269 10 0.4818746 -1.72143092 -2.19579027 2.0118824 -0.5705269 12 2.8519611

Hello, I have two questions concerning the RWeka package: 1.) First question: How can one perform a cross validation, -say 10fold- for a given data set and given model ? 2.) Second question What is the correct syntax for the parametrization of e.g. Kernel classifiers interface m1 <- SMO(Species ~ ., data = iris, control =

Hi all, I'm having this error, since I'm working with a data matrix I don't understand what's happening; I've tried several ways to solve this, even working with sparse matrix, but nothing seems to solve it, I've also tried svm (with a simple matrix 3*3 and still got the same error. > dados<-read.table("b.txt",sep="",nrows=30000) >

Hi all, sorry for my english, but I don't speak yours language. I'm trying to use bart() and rbf(). The package I'm using now is "BayesTree" and "neural", respectively. I could create the models, but I can't predict my test data. Does anyone have such an experience? Any advice is appreciated! Thank you in advanced!. Andr? -- View this message in

Hi!! I am trying to figure out how to use the string kernel "stringdot" in kernlab. k <- function(x,y) { (sum(x*y) +1)*exp(-0.001*sum((x-y)^2)) } class(k) <- "kernel" data(promotergene) ## train svm using custom kernel gene.k <- ksvm(Class~.,data=promotergene,kernel=k,C=10,cross=5) # works fine in this case gene.rbf <-

Dear community, I have a problem with a string conversion: > text [1] "" "and" "\xc1d\xe1m" [4] "graphical" "interface" "MLP" [7] "Nagy" "networks" "Networks" [10] "neural" "Neural"

Hi, My question might be a little general. I have a number of values to select for the complexity parameters in some classifier, e.g. the C and gamma in SVM with RBF kernel. The selection is based on which values give the smallest cross validation error. I wonder if the randomized splitting of the available dataset into folds is done only once for all those choices for the parameter values, or

Is there a method to list the components of an object, instead of looking at the help for that method? Let me be more clear with an example data(iris) ## tune `svm' for classification with RBF-kernel (default in svm), ## using one split for training/validation set obj <- tune(svm, Species~., data = iris, ranges = list(gamma = 2^(-1:1), cost = 2^(2:4)),

I have a data set with about 30,000 training cases and 103 variable. I've trained an SVM (using the e1071 package) for a binary classifier {0,1}. The accuracy isn't great. I used a grid search over the C and G parameters with an RBF kernel to find the best settings. I remember that for least squares, R has a nice stepwise function that will try combining subsets of variables to find

Dear R users and developers, Would any of you be interested in giving a lecture about R and/or R use cases at the following free software conference that takes place in Amiens, France, next summer? We already had a talk on R last year by Yves Croissant (http://2006.rmll.info/theme_26?lang=en) but are still open to any submission this year. We expect some talks this year (to be confirmed) about

Materiel : pc OS : Linux (Mandrake 10.0) Wine Version : 2004 02 13 I am studying Wine and when I want to install Office 2000 with Wine (from the cdrom or from the hard disk) , the install crashes with this message : " error 1311. Cannot find the source file : D:\OFFCD1_2.CAB. Check if this file exist and if you can access to it " But this file doesn't exist ! the cdrom

When I try to crate a grid of parameters for training with caret I get various errors: ------------------------------------------------------------ > my_grid <- createGrid("rf") Error in if (p <= len) { : argument is of length zero > my_grid <- createGrid("rf", 4) Error in if (p <= len) { : argument is of length zero > my_grid <-

On Mon 3 Sep 4:04 pm Ivo Emanuel Gon?alves wrote: > > can the flac encoder be used to compress non-wave data? > No, it's not possible. ?That's actually very silly. Actually, there is no reason it should not run on the data fine, if presented to it appropriately. Input data is a binary stream, and any input will work correctly. With music data, most algorithms rely on the fact

I receive stdin input from "samba user syncpasswords" in my python script. The user is created with ' Active Directory Users and Computers', and have some accentuated characters in their givenName and/or familyName (sn) When parsing the diff, the CN reads of, but weird characters appears in the attributes instead of the right name : INFO:root:DN found: CN=Arsène

Hi, I am currently running this version of wine (wine-20031118-1rh9winehq.i386.rpm) on a RH9 OS. I installed MS Word 2000 and everything went well. However, every time I run MS Word, the configuration setup screen would appear. But after that, it seems that MS Word runs OK. There are also a number of messages coming out (see below). Can anyone help me stop the configuration setup from

Dear list I've a generic question about how to tune an SVM I'm trying to classify with caret package some population data from a case-control study . In each column of my matrix there are the SNP genotypes , in each row there are the individuals. I correctly splitted my total dataset in training(132 individuals) and test (50 individuals) (respecting the total observed genotypic

I would like to code the following in R: a1(b1+b2+b3) + a2(b1+b3+b4) + a3(b1+b2+b4) + a4(b1+b2+b3) or in summation notation: sum_{i=1, j\neq i}^{4} a_i * b_i I realise this is the same as: sum_{i=1, j=1}^{4} a_i * b_i - sum_{i=j} a_i * b_i would appreciate some help. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/summation-coding-tp4646678.html Sent from the R

On 6 December 2014 at 00:03, Benjamin Kramer <benny.kra at gmail.com> wrote: > Reverted for now. Not sure what's going on there. Sorry for the breakage. No worries, at least that was easy to spot. Huzzah for buildbots! :) cheers, --renato

Hi all, I have a problem using rdirichlet{gtools}. For Dir( a1, a2, ..., a_n), its mode can be found at $( a_i -1)/ ( \sum_{i}a_i - n)$; The means are $a_i / (\sum_{i} a_i ) $; I tried to study the above properties using rdirichlet from gtools. The code are: ############## library(gtools) alpha = c(1,3,9) #totoal=13 mean.expect = c(1/13, 3/13, 9/13) mode.expect = c(0, 2/10, 8/10) #

Hello everybody, I'm looking for a way to build an RBF classification network with R but I can't find any. I know there is the 'neural' package, but apparently the RBF networks I can build with that are for approximation tasks only. Is there any package I can use to build an RBF network for a classification task? I've also looked on CRAN but couldn't find any. Thank you for