gemseo / mlearning / transform / dimension_reduction

dimension_reduction module

Dimension reduction as a generic transformer.

The DimensionReduction class implements the concept of dimension reduction.

See also

pca

Classes:

DimensionReduction([name, n_components])

Dimension reduction.

class gemseo.mlearning.transform.dimension_reduction.dimension_reduction.DimensionReduction(name='DimensionReduction', n_components=5, **parameters)[source]

Bases: gemseo.mlearning.transform.transformer.Transformer

Dimension reduction.

Attributes
  • name (str) – The name of the transformer.

  • parameters (str) – The parameters of the transformer.

Parameters
  • name (str) – A name for this transformer.

  • n_components (int) – The number of components of the latent space.

  • **parameters – The parameters of the transformer.

  • parameters (Optional[Union[float,int,str,bool]]) –

Return type

None

Attributes:

CROSSED

n_components

The number of components.

Methods:

compute_jacobian(data)

Compute Jacobian of transformer.transform().

compute_jacobian_inverse(data)

Compute Jacobian of the transformer.inverse_transform().

duplicate()

Duplicate the current object.

fit(data, *args)

Fit the transformer to the data.

fit_transform(data, *args)

Fit the transformer to the data and transform the data.

inverse_transform(data)

Perform an inverse transform on the data.

transform(data)

Transform the data.

CROSSED = False
compute_jacobian(data)

Compute Jacobian of transformer.transform().

Parameters

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

Returns

The Jacobian matrix.

Return type

NoReturn

compute_jacobian_inverse(data)

Compute Jacobian of the transformer.inverse_transform().

Parameters

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

Returns

The Jacobian matrix.

Return type

NoReturn

duplicate()

Duplicate the current object.

Returns

A deepcopy of the current instance.

Return type

gemseo.mlearning.transform.transformer.Transformer

fit(data, *args)[source]

Fit the transformer to the data.

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

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

  • args (Union[float, int, str]) –

Returns

The transformed data.

Return type

numpy.ndarray

inverse_transform(data)

Perform an inverse transform on the data.

Parameters

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

Returns

The inverse transformed data.

Return type

NoReturn

property n_components

The number of components.

transform(data)

Transform the data.

Parameters

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

Returns

The transformed data.

Return type

NoReturn