lvq3(x, cl, codebk, niter=10 * n, alpha=0.03, win=0.3, epsilon=0.1)
x
| a matrix or data frame of examples |
cl
| a vector or factor of classifications for the examples |
codebk
| a codebook |
niter
| number of iterations |
alpha
| constant for training |
win
| a tolerance for the closeness of the two nearest vectors. |
epsilon
| proportion of move for correct vectors |
niter
examples at random with replacement, and adjusts the nearest
two examples in the codebook for each.
x
and cl
giving the examples and classes.
Kohonen, T. (1995) Self-Organizing Maps. Springer, Berlin.
lvqinit
, lvq1
, olvq1
, lvq2
, lvqtest
data(iris3) train <- rbind(iris3[1:25,,1],iris3[1:25,,2],iris3[1:25,,3]) test <- rbind(iris3[26:50,,1],iris3[26:50,,2],iris3[26:50,,3]) cl <- factor(c(rep("s",25),rep("c",25), rep("v",25))) cd <- lvqinit(train, cl, 10) lvqtest(cd, train) cd0 <- olvq1(train, cl, cd) lvqtest(cd0, train) cd3 <- lvq3(train, cl, cd0) lvqtest(cd3, train)