morphoclass.transforms.scalers.standard_scaler module

Implementation of the standard scaler transform.

class morphoclass.transforms.scalers.standard_scaler.FeatureStandardScaler(feature_indices, with_mean=True, with_std=True, **kwargs)

Bases: morphoclass.transforms.scalers.abstract_scaler.AbstractFeatureScaler

Scaler that removes the mean and standard deviation.

Internally the StandardScaler from scikit-learn is applied

Parameters

  • feature_indices – List of indices of the feature maps to which to apply the scaling.

  • with_mean (bool (optional)) – Whether or not to shift by the mean value. This value is passed through to the StandardScaler class in sklearn.

  • with_std (bool (optional)) – Whether or not to scale by the standard deviation. This value is passed through to the StandardScaler class in sklearn.

  • kwargs – Additional keyword argument to pass through to the AbstractFeatureScaler base class.

get_config()

Generate the configuration necessary for reconstructing the scaler.

Returns

config – The configuration of the scaler. It should contain all information necessary for reconstructing the scaler using the scaler_from_config function.

Return type

dict

reconstruct(params)

Reconstruct the configuration from parameters.

Parameters

params (dict) – The parameters found in config[“params”] with the config being the dictionary returned by get_config.