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condense {class}

Condense training set for k-NN classifier
Package: 
class
Version: 
7.3-9

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.

Values

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])

Documentation reproduced from package class, version 7.3-9. License: GPL-2 | GPL-3