| lvq2(class) | R Documentation |
Moves examples in a codebook to better represent the training set.
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. |
Selects niter examples at random with replacement, and adjusts the nearest
two examples in the codebook if one is correct and the other incorrect.
A codebook, represented as a list with components x and cl
giving the examples and classes.
Kohonen, T. (1990) The self-organizing map. Proc. IEEE 78, 1464-1480.
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)