minmax_scaling: Compute the min-max scaling

In andreaskapou/processHTS: Process HTS Files and Data

Description

minmax_scaling normalizes a given vector using the the min-max scaling method. More formally:

scaled = \frac{data -x_{min}}{x_{max} - x_{min}} \times (f_{max} - f_{min}) + f_{min}

Usage

minmax_scaling(data, xmin = NULL, xmax = NULL, fmin = 0, fmax = 1)

Arguments

data	Vector with numeric data to be scaled.
xmin	Optional minimum value, otherwise min(data) will be used.
xmax	Optional maximum value, otherwise max(data) will be used.
fmin	Optional minimum range value, default is 0.
fmax	Optional maximum range value, default is 1.

Value

The scaled data in the given range, default is between (0, 1). If xmin = xmax the input vector data is returned.

Author(s)

C.A.Kapourani [e-mail]

Examples

data <- c(-20, 0, 15, 20)
scaled <- minmax_scaling(data)

andreaskapou/processHTS documentation built on May 12, 2019, 3:33 a.m.