lvq2(x, cl, codebk, niter=10 * n, alpha=0.03, win=0.3)
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. |
niter
examples at random with replacement, and adjusts the nearest
two examples in the codebook if one is correct and the other incorrect.x
and cl
giving the examples and classes.Kohonen, T. (1995) Self-Organizing Maps. Springer, Berlin.
lvqinit
, lvq1
, olvq1
, lvq3
, 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) cd2 <- lvq2(train, cl, cd0) lvqtest(cd2, train)