condense {class} | R Documentation |
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
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])
[Package class version 7.3-22 Index]