class_docstr: Class defining ordinal distribution type functionality
docstr: Inverse cumulative link returns the probability of each category.
  
  Args:
      X_hat: Reconstructed data in the latent space.
  
  Returns:
      Modified X_hat.
      MUST be same shape as passed in data.
      Projects the self.idx column from the latent space to the dist_type space.
code: def inverse_link_function(self, X_hat: torch.Tensor) -> torch.Tensor:
      """
      Inverse cumulative link returns the probability of each category.
  
      Args:
          X_hat: Reconstructed data in the latent space.
  
      Returns:
          Modified X_hat.
          MUST be same shape as passed in data.
          Projects the self.idx column from the latent space to the dist_type space.
      """
      return self._get_probs(X_hat)
  
file_path: causalnex/causalnex/structure/pytorch/dist_type/ordinal.py
imports: from copy import deepcopy
  import numpy
  import torch
  from sklearn.preprocessing import OrdinalEncoder
  from causalnex.structure.pytorch.dist_type._base import DistTypeBase
label_desc: Use image node_id 4 for calling the DistTypeOrdinal obj's underlying member method code with example usage: obj.inverse_link_function(X_hat) and returns: self