code: def __init__(self) -> None:
      super().__init__()
      self._variable_keys = self._variable_keys.union({"X"})
      return
  
imports: import datetime
  import gc
  import logging
  import time
  import traceback
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import pandas
  from joblib.memory import Memory
  from sklearn.base import clone
  from pycaret.containers.metrics.clustering import get_all_metric_containers
  from pycaret.containers.models.clustering import ALL_ALLOWED_ENGINES, get_container_default_engines
  from pycaret.internal.display import CommonDisplay
  from pycaret.internal.logging import get_logger, redirect_output
  from pycaret.internal.pipeline import Pipeline
  from pycaret.internal.pipeline import estimator_pipeline, get_pipeline_fit_kwargs
  from pycaret.internal.preprocess.preprocessor import Preprocessor
  from pycaret.internal.pycaret_experiment.tabular_experiment import _TabularExperiment
  from pycaret.internal.validation import is_sklearn_pipeline
  from pycaret.loggers.base_logger import BaseLogger
  from pycaret.utils.constants import DATAFRAME_LIKE, SEQUENCE_LIKE
  from pycaret.utils.generic import MLUsecase, highlight_setup
label_desc: Use image node_id 1 to create a new _UnsupervisedExperiment object from inherited base classes: _TabularExperiment, Preprocessor with example: obj = _UnsupervisedExperiment()