lvqinit {class}R Documentation

Initialize a LVQ Codebook


Construct an initial codebook for LVQ methods.


lvqinit(x, cl, size, prior, k = 5)


x a matrix or data frame of training examples, n by p.
cl the classifications for the training examples. A vector or factor of length n.
size the size of the codebook. Defaults to min(round(0.4*ng*(ng-1 + p/2),0), n) where ng is the number of classes.
prior Probabilities to represent classes in the codebook. Default proportions in the training set.
k k used for k-NN test of correct classification. Default is 5.


Selects size examples from the training set without replacement with proportions proportional to the prior or the original proportions.


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.

Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

lvq1, lvq2, lvq3, olvq1, lvqtest


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)
cd1 <- olvq1(train, cl, cd)
lvqtest(cd1, train)

[Package class version 7.2-23 Index]