ubENN: Edited Nearest Neighbor

In unbalanced: Racing for Unbalanced Methods Selection

Description

Edited Nearest Neighbor removes any example whose class label differs from the class of at least two of its three nearest neighbors.

Usage

ubENN(X, Y, k = 3, verbose = TRUE)

Arguments

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)

Details

In order to compute nearest neighbors, only numeric features are allowed.

Value

The function returns a list:

X	input variables
Y	response variable

References

D. Wilson. Asymptotic properties of nearest neighbor rules using edited data. Systems, Man and Cybernetics, IEEE Transactions on, 408-421, 1972.

See Also

ubBalance

Examples

library(unbalanced)
data(ubIonosphere)
n<-ncol(ubIonosphere)
output<-ubIonosphere$Class
input<-ubIonosphere[ ,-n]

data<-ubENN(X=input, Y= output)
newData<-cbind(data$X, data$Y)

Example output

Loading required package: mlr
Loading required package: ParamHelpers
Loading required package: foreach
Loading required package: doParallel
Loading required package: iterators
Loading required package: parallel
Number of instances removed from majority class with ENN: 2 	 Time needed: 0.02 

unbalanced documentation built on May 2, 2019, 7:01 a.m.