pyanno4rt.learning_model.preprocessing.transformers._whitening
Whitening transformer.
Overview
Whitening transformer class. |
Classes
- class pyanno4rt.learning_model.preprocessing.transformers._whitening.Whitening(method='zca')[source]
Whitening transformer class.
This class provides methods to fit, transform and gradientize the input features by their whitening matrix.
- Parameters:
method ({'pca', 'zca'}, default='zca') –
Method for the computation of the whitening matrix.
’zca’ : zero-phase component analysis (Mahalanobis transformation)
’pca’ : principal component analysis
- method
See ‘Parameters’.
- Type:
{‘pca’, ‘zca’}
- means
Mean values of the features.
- Type:
ndarray
- matrix
Whitening matrix.
- Type:
ndarray
Overview
Methods fit(features, labels)Fit the whitening transformer.
transform(features, labels)Transform the input features/labels.
compute_gradient(features)Compute the whitening transformer gradient w.r.t the input features.
Members
- fit(features, labels)[source]
Fit the whitening transformer.
- Parameters:
features (ndarray) – Values of the input features.
labels (None or ndarray) – Values of the input labels.
- transform(features, labels)[source]
Transform the input features/labels.
- Parameters:
features (ndarray) – Values of the input features.
labels (None or ndarray) – Values of the input labels.
- Returns:
ndarray – Transformed values of the input features.
None or ndarray – Transformed values of the input labels.