search for: lcrab

Can anyone explain the root of my problem? When I type the following code into R, I receive 42 support vectors insted of the 21 stated in the book 'Modern Applied Statistics with S': library(MASS); library(e1071); library(class); lcrabs <- log(crabs[,4:8]); (svm(crabs$sp ~ ., data = lcrabs, cost = 100, gamma = 1)); By changing the value of gamma I can obtain only 21 support vectors, but I not sure where an explanation to my problem can be found. I use R 2.3.2 and the most recent version of the package 'e1071'. My goal...

I've been experimenting with the lattice graphics in chapter 3 of MASS. The code to produce figure 3.14 is: data(crabs) library(mva) lcrabs.pc <- predict(princomp(log(crabs[,4:8]))) crabs.grp <- c("B", "b", "O", "o")[rep(1:4, rep(50,4))] splom( ~lcrabs.pc[, 1:3], groups = crabs.grp, panel = panel.superpose, key = list(text = list(c("Blue male", "Blue female",...

Hi all, I have a question about the SOM routine. You can either supply the initial representatives for the lattice yourself or else they are chosen randomly from the dataset. Is it possible to pass the random-seed as an argument somehow, when choosing the random initialisation of the lattice? As it is now, each time I run a SOM on a dataset with the same settings the resulting SOM will still

I'm trying to learn how to create Trellis multi-panel plots, but I'm having some trouble reproducing the graphs shown in Venables & Ripley (2002) (e.g., Figs 4.14 & 4.15). Actually, everything looks fine except for the fact that I can't see any text above the individual panels. I'm using R 1.9.0 for OS-X running on Mac OSX 10.3.3, and I'm drawing the graphs into

Dear R users, I want to do discriminant analysis on my data. I have successfully followed the discriminant analysis in V & R on the iris data: > ir <- rbind (iris3[,,1],iris3[,,2],iris3[,,3]) > ir.species <- c(rep("s",50),rep("c",50),rep("v",50)) > a <- lda(log(ir),ir.species) > a$svd^2/sum(a$svd^2) [1] 0.996498601 0.003501399 > a.x <-