class_docstr: Abstract class for all combination classes.
  
  Parameters
  ----------
  base_estimators: list, length must be greater than 1
      A list of base estimators. Certain methods must be present, e.g.,
      `fit` and `predict`.
  
  pre_fitted: bool, optional (default=False)
      Whether the base estimators are trained. If True, `fit`
      process may be skipped.
docstr: Get parameter names for the estimator
  
  See http://scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html
  and sklearn/base.py for more information.
docstr_tok: ["Get","parameter","names","for","the","estimator","See","http",":","\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.base.BaseEstimator.html","and","sklearn\/base.py","for","more","information","."]
code: def _get_param_names(cls):
      # noinspection PyPep8
      """Get parameter names for the estimator
  
      See http://scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html
      and sklearn/base.py for more information.
      """
  
      # fetch the constructor or the original constructor before
      # deprecation wrapping if any
      init = getattr(cls.__init__, "deprecated_original", cls.__init__)
      if init is object.__init__:
          # No explicit constructor to introspect
          return []
  
      # introspect the constructor arguments to find the model parameters
      # to represent
      init_signature = signature(init)
      # Consider the constructor parameters excluding 'self'
      parameters = [
          p
          for p in init_signature.parameters.values()
          if p.name != "self" and p.kind != p.VAR_KEYWORD
      ]
      for p in parameters:
          if p.kind == p.VAR_POSITIONAL:
              raise RuntimeError(
                  "scikit-learn estimators should always "
                  "specify their parameters in the signature"
                  " of their __init__ (no varargs)."
                  " %s with constructor %s doesn't "
                  " follow this convention." % (cls, init_signature)
              )
      # Extract and sort argument names excluding 'self'
      return sorted([p.name for p in parameters])
  
imports: import warnings
  from collections import defaultdict
  from abc import ABC, abstractmethod
  import numpy
  from numpy import percentile
  from scipy.special import erf
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.utils import column_or_1d
  from sklearn.utils.validation import check_is_fitted
  from sklearn.utils.multiclass import check_classification_targets
  from .sklearn_base import _pprint
  from inspect import signature
label_desc: Use image node_id 14 for calling the BaseAggregator obj's underlying member method code with example usage: obj._get_param_names(cls) and returns: sorted, list