Initialize a LVQ Codebook

DESCRIPTION:

Construct an initial codebook for LVQ methods.

USAGE:

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

REQUIRED ARGUMENTS:

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.

OPTIONAL ARGUMENTS:

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.

VALUE:

A codebook, represented as a list with components x and cl giving the examples and classes.

DETAILS:

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

REFERENCES:

Kohonen, T. (1990) The self-organizing map. Proc. IEEE 78, 1464-1480.

Kohonen, T. (1995) Self-Organizing Maps. Springer, Berlin.

SEE ALSO:

, , , ,

EXAMPLES:

train <- rbind(iris[1:25,,1],iris[1:25,,2],iris[1:25,,3])
test <- rbind(iris[26:50,,1],iris[26:50,,2],iris[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)