similar to: SVM error

Hi, I have 35 data files for reading. I would like get a program for performing reading of 35 files at once. All are of the type: Dados1.raw, Dados2.raw and so on. If the files have the same number of columns, I can read with the following commands: rm(list=ls()) filenames = list.files(path="~/Silvano/Arq", pattern="Dados+.*raw") names = substr(filenames, 1, 7) for(i in

Dear R Community, I'm trying to write a loop to split my data into different series. I need to make a new matrix (or series) according to the series code. For instance, every time the "code" column assumes the value "433" I need to save "date", "value", and "code" into the "dados433" matrix. Please take a look at the following

Hi, I'm doing kolmogorv-smirnov test but I don't know what conclusions to take, I want to know if my data has a normal distribution: > ks.test(dados1,"pnorm") One-sample Kolmogorov-Smirnov test data: dados1 D = 0.972, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: cannot compute correct p-values with ties in: ks.test(dados1,

Dear R Discussion List, I would like to save my data as a xlsx file. But at first I need to split it and then save each series into a Excel column. Please take a look at the following code: dados <- data.frame(matrix(c("2012-01-01","2012-02-01", "2012-03-01","2012-04-01","2012-05-01","2012-06-01",

Dear R helpers,   I am a beginner at R so please be gentle :) I have already read manuals and FAQs, with no help. I have a monthly time series data on public debt with 40 variables, it starts on January 1994 and ends on June 2011. I am loading the data into R using read.csv and the data looks ok when I do edit(dados): > dados<-read.csv("dadosR3.csv", header=T) then I tried making

Hi all, I'm working with some data: 54 variables and a column of classes, each observation as one of a possible seven different classes: > var.can3<-lda(x=dados[,c(1:28,30:54)],grouping=dados[,55],CV=TRUE) Warning message: In lda.default(x, grouping, ...) : variables are collinear > summary(var.can3) Length Class Mode class 30000 factor numeric ### why?? I

Hi all, Sorry to be bothering again with probably an easy error to fix, but I've been trying to solve the problem and haven't been able yet to do it. So I'm doing this: > dados<-read.table("b.txt",sep="",nrows=30000) >

Hi, I would like to know if there is an algorithm in R for testing if a data set as a normal destribution. Thank you for your time, Pedro Marques

Hi, I have a dummy question. Suppose that I have two explanatory variable, T1 (A, B) and T2 (C, D) and one response variable. > attach(dados) > tapply(Y,list(T1,T2),mean) C D A 2.200000 10.20000 B 2.223333 20.26667 In this case, "A" and "B" inside "C" have no difference, but have differences inside "D" I make this model: > m

2017-06-26 10:38 GMT-03:00 Rowland Penny via samba <samba at lists.samba.org>: > Your 'samba' password and your windows password MUST be the same to > allow you to connect to a Samba share from a Windows machine without > being prompted for a password. I do not understand why, after being > prompted for the correct username & password, that it doesn't connect,

Hi all, I don't know how to choose the formula to use when plotting an svm model, I think I'm using the wrong one and so that is why I'm having trouble. I should be very grateful if someone could help me on this.. > dados<-read.table("b.txt",sep="",nrows=30000) >

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

Hi all, I'm trying to plot an svm model and I'm the following error: > plot(model, data= dados[,-1], formula=formula(dados[,2]~dados[,3]),svSymbol = 1, dataSymbol = 2, symbolPalette = rainbow(4),color.palette = terrain.colors) Error in terms.default(x) : no terms component Anyone knows how to solve this??? Best regards, Pedro Marques

Dear helpers I constructed a data frame with this structure > str(dados1) `data.frame': 485 obs. of 16 variables: $ Emissor : int 1 1 1 1 1 1 1 1 1 1 ... $ Marisca.Rio : int 1 1 1 1 1 1 1 1 1 1 ... $ Per?odo : int 1 1 1 1 1 1 1 1 1 1 ... $ Reproducao : int 3 3 3 3 3 3 3 3 3 3 ... $ Estacao : int 2 2 2 2 2 2 2 2 2 2 ... $ X30cm : int

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

----- Original Message ----- From: "Silvano" <silvano at uel.br> To: <r-help at r-project.org> Sent: Thursday, June 30, 2011 9:07 AM Subject: Tables and merge > Hi, > > I have 21 files which is common variable CODE. > Each file refers to a question. > > I would like to join the 21 files into one, to construct > tables for each question by CODE. >

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, I'm working with a numeric matrix with 55columns and 581012 rows and I'm having problems in allocation of memory using some of the functions in R: for example lda, rda (library MASS), princomp(package mva) and mvnorm.etest (energy package). I've read tips to use less memory in help(read.table) and managed to use some of this functions, but haven't been able to work with

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

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