gemseo.mlearning.transformers.scaler.min_max_scaler module#
Scaling a variable with a geometrical linear transformation.
The MinMaxScaler class implements the MinMax scaling method
applying to some parameter \(z\):
\[\bar{z} := \text{offset} + \text{coefficient}\times z
= \frac{z-\text{min}(z)}{(\text{max}(z)-\text{min}(z))},\]
where \(\text{offset}=-\text{min}(z)/(\text{max}(z)-\text{min}(z))\) and \(\text{coefficient}=1/(\text{max}(z)-\text{min}(z))\).
In the MinMax scaling method, the scaling operation linearly transforms the original variable \(z\) such that the minimum of the original data corresponds to 0 and the maximum to 1.
Warning
When \(\text{min}(z)=\text{max}(z)\neq 0\), we use \(\bar{z}=\frac{z}{\text{min}(z)}-0.5\). When \(\text{min}(z)=\text{max}(z)=0\), we use \(\bar{z}=z+0.5\).