SMOTEWB (version 1.2.0)

SMOTE: Synthetic Minority Oversampling Technique (SMOTE)

Description

Resampling with SMOTE.

Usage

SMOTE(x, y, k = 5)

Value

a list with resampled dataset.

x_new

Resampled feature matrix.

y_new

Resampled target variable.

x_syn

Generated synthetic feature data.

y_syn

Generated synthetic label data.

Arguments

x

feature matrix.

y

a factor class variable with two classes.

k

number of neighbors. Default is 5.

Author

Fatih Saglam, [e-mail]

Details

SMOTE (Chawla et al., 2002) is an oversampling method which creates links between positive samples and nearest neighbors and generates synthetic samples along that link.

It is well known that SMOTE is sensitive to noisy data. It may create more noise.

Can work with classes more than 2.

Note: Much faster than smotefamily::SMOTE().

References

Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002). SMOTE: synthetic minority over-sampling technique. Journal of artificial intelligence research, 16, 321-357.

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 <- SMOTE(x = x, y = y, k = 7)

plot(m$x_new, col = m$y_new)