code: def fit(self, X, y=None, **params):
          '''
          Fit the transformer on the stacked points.
  
          Parameters
          ----------
          X : :class:`Features` or list of arrays of shape ``[n_samples[i], n_features]``
              Training set. If a Features object, it will be stacked.
  
          any other keyword argument :
              Passed on as keyword arguments to the transformer's ``fit()``.
          '''
          X = as_features(X, stack=True)
          self.transformer.fit(X.stacked_features, y, **params)
          return self fit(self, X, y=None, **params):
          '''
          Fit the transformer on the stacked points.
  
          Parameters
          ----------
          X : :class:`Features` or list of arrays of shape ``[n_samples[i], n_features]``
              Training set. If a Features object, it will be stacked.
  
          any other keyword argument :
              Passed on as keyword arguments to the transformer's ``fit()``.
          '''
          X = as_features(X, stack=True)
          self.transformer.fit(X.stacked_features, y, **params)
          return self
docs: Fit the transformer on the stacked points.
  
          Parameters
          ----------
          X : :class:`Features` or list of arrays of shape ``[n_samples[i], n_features]``
              Training set. If a Features object, it will be stacked.
  
          any other keyword argument :
              Passed on as keyword arguments to the transformer's ``fit()``.