Usage
RUS(x, y, n_neededToRemove = NULL, ...)
Arguments
- x
feature matrix.
- y
a factor class variable. Can have more than two classes.
- n_neededToRemove
vector of desired number removal for each class.
A vector of integers for each class. Default is NULL meaning full balance.
Must be equal or lower than the number of samples in each class.
- ...
not used.
Value
a list with resampled dataset.
- x_new
Resampled feature matrix.
- y_new
Resampled target variable.
Details
Random Undersampling (RUS) is a method of removing negative
samples until balance is achieved.
Can work with classes more than 2.
Author
Fatih Saglam, saglamf89@gmail.com
Examples
set.seed(1)
x <- rbind(matrix(rnorm(2000, 3, 1), ncol = 2, nrow = 1000),
matrix(rnorm(100, 5, 1), ncol = 2, nrow = 50))
y <- as.factor(c(rep("negative", 1000), rep("positive", 50)))
plot(x, col = y)
# resampling
m <- RUS(x = x, y = y)
plot(m$x_new, col = m$y_new)
