gemseo / mlearning / transform / 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.

class gemseo.mlearning.transform.scaler.min_max_scaler.MinMaxScaler(name='MinMaxScaler', offset=0.0, coefficient=1.0)

Bases: Scaler

Min-max scaler.

Parameters:

• name (str) –

  A name for this transformer.

  By default it is set to “MinMaxScaler”.

• offset (float) –

  The offset of the linear transformation.

  By default it is set to 0.0.

• coefficient (float) –

  The coefficient of the linear transformation.

  By default it is set to 1.0.

compute_jacobian(data)

Compute Jacobian of transformer.transform().

Parameters:

data (ndarray) – The data where the Jacobian is to be computed.

Returns:

The Jacobian matrix.

Return type:

ndarray

compute_jacobian_inverse(data)

Compute Jacobian of the transformer.inverse_transform().

Parameters:

data (ndarray) – The data where the Jacobian is to be computed.

Returns:

The Jacobian matrix.

Return type:

ndarray

duplicate()

Duplicate the current object.

Returns:

A deepcopy of the current instance.

Return type:

Transformer

fit(data, *args)

Fit the transformer to the data.

Parameters:

• data (ndarray) – The data to be fitted.

• args (Union[float, int, str]) –

Return type:

NoReturn

fit_transform(data, *args)

Fit the transformer to the data and transform the data.

Parameters:

• data (ndarray) – The data to be transformed.

• args (Union[float, int, str]) –

Returns:

The transformed data.

Return type:

ndarray

inverse_transform(data)

Perform an inverse transform on the data.

Parameters:

data (ndarray) – The data to be inverse transformed.

Returns:

The inverse transformed data.

Return type:

ndarray

transform(data)

Transform the data.

Parameters:

data (ndarray) – The data to be transformed.

Returns:

The transformed data.

Return type:

ndarray

CROSSED = False

property coefficient: float

The scaling coefficient.

name: str

The name of the transformer.

property offset: float

The scaling offset.

parameters: str

The parameters of the transformer.

Examples using MinMaxScaler

Quality measure for surrogate model comparison

Quality measure for surrogate model comparison

Mixture of experts

Mixture of experts

Scaler example

Scaler example