standard_scaler module¶
Scaling a variable with a statistical linear transformation.
The StandardScaler class implements the Standard scaling method
applying to some parameter \(z\):
\[\bar{z} := \text{offset} + \text{coefficient}\times z
= \frac{z-\text{mean}(z)}{\text{std}(z)}\]
where \(\text{offset}=-\text{mean}(z)/\text{std}(z)\) and \(\text{coefficient}=1/\text{std}(z)\).
In this standard scaling method, the scaling operation linearly transforms the original variable math:z such that in the scaled space, the original data have zero mean and unit standard deviation.
Warning
When \(\text{std}(z)=0\) and \(\text{mean}(z)\neq 0\), we use \(\bar{z}=\frac{z}{\text{mean}(z)}-1\). When \(\text{std}(z)=0\) and \(\text{mean}(z)=0\), we use \(\bar{z}=z\).
- class gemseo.mlearning.transformers.scaler.standard_scaler.StandardScaler(name='', offset=0.0, coefficient=1.0)[source]
Bases:
ScalerStandard scaler.
- Parameters:
- name: str
The name of the transformer.
