ubSMOTE | R Documentation |
Function that implements SMOTE (synthetic minority over-sampling technique)
ubSMOTE(X, Y, perc.over = 200, k = 5, perc.under = 200, verbose = TRUE)
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. |
perc.over |
per.over/100 is the number of new instances generated for each rare instance. If perc.over < 100 a single instance is generated. |
k |
the number of neighbours to consider as the pool from where the new examples are generated |
perc.under |
perc.under/100 is the number of "normal" (majority class) instances that are randomly selected for each smoted observation. |
verbose |
print extra information (TRUE/FALSE) |
Y must be a factor.
The function returns a list:
X |
input variables |
Y |
response variable |
Original code from DMwR package
Chawla, Nitesh V., et al. "SMOTE: synthetic minority over-sampling technique." arXiv preprint arXiv:1106.1813 (2011).
ubBalance
library(unbalanced) data(ubIonosphere) n<-ncol(ubIonosphere) output<-ubIonosphere$Class input<-ubIonosphere[ ,-n] data<-ubSMOTE(X=input, Y= output) newData<-cbind(data$X, data$Y)
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