
condense  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])


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