Min-Max Normalization

Scales a numeric vector to a specific range, typically [0, 1]. This method is sensitive to outliers.

Usage

norm_minmax(x, min_val = 0, max_val = 1, na.rm = TRUE)

Arguments

x

A numeric vector.

min_val

The minimum value of the target range. Default is 0.

max_val

The maximum value of the target range. Default is 1.

na.rm

Logical. Should NA values be removed during min/max calculation? Default is TRUE.

Value

A numeric vector scaled to the range [min_val, max_val].

Details

Formula: \(x' = \frac{x - \min(x)}{\max(x) - \min(x)} \times (\text{max\_val} - \text{min\_val}) + \text{min\_val}\)

References

Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques (3rd ed.). Morgan Kaufmann.

Examples

norm_minmax(c(1, 2, 3, 4, 5))
#> [1] 0.00 0.25 0.50 0.75 1.00
norm_minmax(c(1, 2, 3), min_val = -1, max_val = 1)
#> [1] -1  0  1