class_docstr: Base class for all estimators in scikit-learn
  
  Notes
  -----
  All estimators should specify all the parameters that can be set
  at the class level in their ``__init__`` as explicit keyword
  arguments (no ``*args`` or ``**kwargs``).
code: def __init_subclass__(cls):
      orig_init = cls.__init__
  
      def init(self, *args, **kwargs):
          handle = kwargs["handle"] if "handle" in kwargs else None
          verbose = kwargs["verbose"] if "verbose" in kwargs else False
          output_type = (
              kwargs["output_type"] if "output_type" in kwargs else None
          )
          Base.__init__(
              self,
              handle=handle,
              verbose=verbose,
              output_type=output_type,
          )
          for param in ["handle", "verbose", "output_type"]:
              if param in kwargs:
                  del kwargs[param]
          orig_init(self, *args, **kwargs)
  
      cls.__init__ = init
  
file_path: cuml/python/cuml/_thirdparty/sklearn/utils/skl_dependencies.py
imports: from cuml.internals.array_sparse import SparseCumlArray
  from ....internals.base import Base
  from ..utils.validation import check_X_y
  from ....thirdparty_adapters import check_array
label_desc: Use image node_id 1 for calling the BaseEstimator obj's underlying member method code with example usage: obj.__init_subclass__(cls) without return types