ubCNN | R Documentation |
Condensed Nearest Neighbor selects the subset of instances that are able to correctly classifing the original datasets using a one-nearest neighbor rule.
ubCNN(X, Y, k = 1, verbose = T)
X |
the input variables of the unbalanced dataset. |
Y |
the response variable of the unbalanced dataset. It must be a binary factor where the majority class is coded as 0 and the minority as 1. |
k |
the number of neighbours to use |
verbose |
print extra information (TRUE/FALSE) |
In order to compute nearest neighbors, only numeric features are allowed.
The function returns a list:
X |
input variables |
Y |
response variable |
P. E. Hart. The condensed nearest neighbor rule. IEEE Transactions on Informa- tion Theory, 1968.
ubBalance
library(unbalanced) data(ubIonosphere) n<-ncol(ubIonosphere) output<-ubIonosphere$Class input<-ubIonosphere[ ,-n] data<-ubCNN(X=input, Y= output) newData<-cbind(data$X, data$Y)
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