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.
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
