class_docstr: A class for feature agglomeration via the transform interface.
docstr: Inverse the transformation and return a vector of size `n_features`.
  
  Parameters
  ----------
  Xt : array-like of shape (n_samples, n_clusters) or (n_clusters,)
      The values to be assigned to each cluster of samples.
  
  Xred : deprecated
      Use `Xt` instead.
  
      .. deprecated:: 1.3
  
  Returns
  -------
  X : ndarray of shape (n_samples, n_features) or (n_features,)
      A vector of size `n_samples` with the values of `Xred` assigned to
      each of the cluster of samples.
code: def inverse_transform(self, Xt=None, Xred=None):
      """
      Inverse the transformation and return a vector of size `n_features`.
  
      Parameters
      ----------
      Xt : array-like of shape (n_samples, n_clusters) or (n_clusters,)
          The values to be assigned to each cluster of samples.
  
      Xred : deprecated
          Use `Xt` instead.
  
          .. deprecated:: 1.3
  
      Returns
      -------
      X : ndarray of shape (n_samples, n_features) or (n_features,)
          A vector of size `n_samples` with the values of `Xred` assigned to
          each of the cluster of samples.
      """
      if Xt is None and Xred is None:
          raise TypeError("Missing required positional argument: Xt")
  
      if Xred is not None and Xt is not None:
          raise ValueError("Please provide only `Xt`, and not `Xred`.")
  
      if Xred is not None:
          warnings.warn(
              (
                  "Input argument `Xred` was renamed to `Xt` in v1.3 and will be"
                  " removed in v1.5."
              ),
              FutureWarning,
          )
          Xt = Xred
  
      check_is_fitted(self)
  
      unil, inverse = np.unique(self.labels_, return_inverse=True)
      return Xt[..., inverse]
  
file_path: scikit-learn/sklearn/cluster/_feature_agglomeration.py
imports: import warnings
  import numpy
  from scipy.sparse import issparse
  from ..base import TransformerMixin
  from ..utils import metadata_routing
  from ..utils.validation import check_is_fitted
label_desc: Use image node_id 2 for calling the AgglomerationTransform obj's underlying member method code with example usage: obj.inverse_transform(Xt, Xred) and returns: Xt