class_docstr: Base class for encoders that includes the code to categorize and
  transform the input features.
code: def _find_infrequent_category_indices(self, Xi):
      # TODO: this is using unique on X again. Ideally we should integrate
      # this into _encode()
      _, counts = np.unique(Xi, return_counts=True)
      return np.argsort(counts)[: -self.max_levels]
  
imports: import copy
  from numbers import Integral
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
  from autogluon.features.generators import LabelEncoderFeatureGenerator
label_desc: Use image node_id 4 for calling the _BaseEncoder obj's underlying member method code with example usage: obj._find_infrequent_category_indices(Xi) and returns: np