pyanno4rt.learning_model.preprocessing.transformers._standard_scaler
Standard scaling transformer.
Overview
Standard scaling transformer class. |
Classes
- class pyanno4rt.learning_model.preprocessing.transformers._standard_scaler.StandardScaler(center=True, scale=True)[source]
Standard scaling transformer class.
This class provides methods to fit, transform and gradientize the input features by their z-score.
- Parameters:
center (bool, default=True) – Indicator for the centering of the data by the mean values.
scale (bool, default=True) – Indicator for the scaling of the data by the standard deviations.
- center
See ‘Parameters’.
- Type:
bool
- scale
See ‘Parameters’.
- Type:
bool
- means
Mean values of the features (if center is false, set to zeros).
- Type:
ndarray
- deviations
Standard deviations of the features (if scale is false, set to ones).
- Type:
ndarray
Overview
Methods fit(features, labels)Fit the standard scaling transformer.
transform(features, labels)Transform the input features/labels.
compute_gradient(features)Compute the standard scaling transformer gradient w.r.t the input features.
Members
- fit(features, labels)[source]
Fit the standard scaling 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.