Min-Max Standardization — MinMaxScaling • lehuynh

Normalize / Standardize / Scale the data to the fixed range from 0 to 1. The minimum value of data gets transformed into 0. The maximum value gets transformed into 1. Other values get transformed into decimals between 0 and 1.

Usage

MinMaxScaling(x, y = x)

Arguments

x: A numeric vector to be scaled.
y: An optional numeric vector used to determine the scaling range. If not provided, the scaling range is determined by the values in x. Default: y = x.

Value

A numeric vector of the same length as x, with values scaled to the range from 0 to 1.

Details

Min-max scaling is a normalization technique that transforms the values in a vector to a standardized range. The scaling is performed using the formula: $scaled_x = \frac{x - \min(y)}{\max(y) - \min(y)}$

Examples


dat1 = seq(from = 5, to = 30, length.out = 6)

MinMaxScaling(dat1)
#> [1] 0.0 0.2 0.4 0.6 0.8 1.0

dat2 = c(7, 13, 22)

MinMaxScaling(x = dat2, y = dat1)
#> [1] 0.08 0.32 0.68