RUS: Random Undersampling (RUS)

In SMOTEWB: Imbalanced Resampling using SMOTE with Boosting (SMOTEWB)

Random Undersampling (RUS)

Description

Resampling with RUS.

Usage

RUS(x, y, n_neededToRemove = NULL)

Arguments

x	feature matrix.
y	a factor class variable with 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.

Details

Random Undersampling (RUS) is a method of removing negative samples until balance is achieved.

Can work with classes more than 2.

Value

a list with resampled dataset.

x_new	Resampled feature matrix.
y_new	Resampled target variable.

Author(s)

Fatih Saglam, [e-mail]

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)

SMOTEWB documentation built on June 8, 2025, 11:57 a.m.