condense: Condense training set for k-NN classifier

In class: Functions for Classification

Condense training set for k-NN classifier

Description

Condense training set for k-NN classifier

Usage

condense(train, class, store, trace = TRUE)

Arguments

train	matrix for training set
class	vector of classifications for test set
store	initial store set. Default one randomly chosen element of the set.
trace	logical. Trace iterations?

Details

The store set is used to 1-NN classify the rest, and misclassified patterns are added to the store set. The whole set is checked until no additions occur.

Value

Index vector of cases to be retained (the final store set).

References

P. A. Devijver and J. Kittler (1982) Pattern Recognition. A Statistical Approach. Prentice-Hall, pp. 119–121.

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

reduce.nn, multiedit

Examples

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)))
keep <- condense(train, cl)
knn(train[keep, , drop=FALSE], test, cl[keep])
keep2 <- reduce.nn(train, keep, cl)
knn(train[keep2, , drop=FALSE], test, cl[keep2])

class documentation built on May 3, 2023, 5:09 p.m.