gemseo / mlearning / transform / scaler

# standard_scaler module¶

## Standard data scaler¶

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.

class gemseo.mlearning.transform.scaler.standard_scaler.StandardScaler(name='StandardScaler', offset=0.0, coefficient=1.0)[source]

Standard scaler.

Constructor.

Parameters
• name (str) – name of the scaler. Default: ‘StandardScaler’.

• offset (float) – offset of the linear transformation. Default: 0.

• coefficient (float) – coefficient of the linear transformation. Default: 1.

fit(data)[source]

Fit offset and coefficient terms from a data array. The mean and standard deviation are computed along the first axis of the data.

Parameters

data (array) – data to be fitted.