[R] Plot error

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

[R] Svm formula

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=3)

[R] Plot.svm error

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=3)

[R] Plot.svm error

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 yet been able to do it. So, I'm doing this: dados-read.table(b.txt,sep=,nrows=3)

[R] SVM error

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.

[R] How to choose the best Kernel in SVM classification

Hi all, I'm working with some data with 54 variables, 44 of them are binary, and I'm using SVM in package e1071 to carry out general classification but I don't know how to choose the best kernel for my data. I would be very grateful if someone could help me on this task. Best regards,

[R] SVM simple error

Hi all, I'm having this simple 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. model-svm(scale=TRUE,type=C,x=dados1,y=dados2,kernel=RBF) Error in

[R] Lda and Qda

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

[R] time series tests

Hi all, Can anyone clear my doubts about what conclusions to take with the following outputs of some time series tests: adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01 alternative hypothesis: stationary Warning

[R] Problems working with large matrix (using package R.huge)

Hi all, Since I was having several problems trying to work with a large matrix I started to use the package R.huge but I'm having the following problem x-FileByteMatrix(covtype.data,nrow=581012,ncol=55) Error: cannot allocate vector of size 770.8 Mb In addition: Warning messages: 1: Reached

[R] time series tests

Hi all, Can anyone clear my doubts about what conclusions to take with the following what puts of some time series tests: adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01 alternative hypothesis: stationary

[R] time series tests

Citando [EMAIL PROTECTED]: Hi all, Can anyone clear my doubts about what conclusions to take with the following outputs of some time series tests: adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01

[R] Testing normality

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

[R] Problems working with large data

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

[R] Binary data sets

Hi, I would like to know if there is any algorithm in R for transforming Binary data sets. I want something like taking all the zeros and giving them some negative value, for example -5, and taking all ones and giving them some positive value, if it had been given -5 for zeros it would be 5

[R] Testing Normal Distributions

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 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the