class_docstr: Meta-estimator to classify on a transformed target.
  
  Parameters
  ----------
  classifier : object, default=None
      Classifier object such as derived from ``ClassifierMixin``. This
      classifier will automatically be cloned each time prior to fitting.
  
  transformer : object, default=None
      Estimator object such as derived from ``TransformerMixin``. Note that the
      transformer will be cloned during fitting. Also, the transformer is
      restricting ``y`` to be a numpy array.
  
  check_inverse : bool, default=True
      Whether to check that ``transform`` followed by ``inverse_transform``
      leads to the original targets.
  
  Attributes
  ----------
  classifier_ : object
      Fitted classifier.
  
  transformer_ : object
      Transformer used in ``fit`` and ``predict``.
  
  Notes
  -----
  This is a modification from TransformedTargetRegressor.
  
  See :ref:`sklearn.compose.TransformedTargetRegressor
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code: def _more_tags(self):
      return {"poor_score": True, "no_validation": True}
  
file_path: pycaret/pycaret/internal/preprocess/target/TransformedTargetClassifier.py
imports: import warnings
  import numpy
  import pandas
  from sklearn.base import BaseEstimator, ClassifierMixin, clone
  from sklearn.exceptions import NotFittedError
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils import _safe_indexing
  from sklearn.utils.validation import _deprecate_positional_args, check_is_fitted, check_X_y
  from .utils import TargetTransformerMixin
label_desc: Use image node_id 5 for calling the TransformedTargetClassifier obj's underlying member method code with example usage: obj._more_tags() and returns: dict