class_docstr: Base class for a Dynamic Classifier Selection (dcs) method.
  All dynamic classifier selection classes should inherit from this class.
  
  Warning: This class should not be used directly, use derived classes
  instead.
code: def _validate_parameters(self):
      super(BaseDCS, self)._validate_parameters()
  
      if not isinstance(self.selection_method, str):
          raise TypeError(
              "The parameter selection_method should be a string."
              " selection_method = ",
              type(self.selection_method),
          )
  
      if self.selection_method not in ["best", "all", "random", "diff"]:
          raise ValueError(
              'Invalid value for parameter "selection_method." '
              "The possible values are: "
              '"best", "all", "random", "diff"'
          )
  
      if not isinstance(self.diff_thresh, float):
          raise TypeError(
              "The parameter diff_thresh should be a float. diff_thresh = ",
              self.diff_thresh,
          )
  
      if (
          self.diff_thresh >= 0.5
          or self.diff_thresh < 0.0
          or np.isnan(self.diff_thresh)
      ):
          raise ValueError(
              "diff_thresh should be lower than 0.5. diff_thresh = ",
              self.diff_thresh,
          )
  
file_path: DESlib/deslib/dcs/base.py
imports: from abc import ABCMeta
  from copy import copy
  import numpy
  from sklearn.utils.validation import check_random_state
  from deslib.base import BaseDS
  from deslib.util.aggregation import majority_voting_rule
label_desc: Use image node_id 6 for calling the BaseDCS obj's underlying member method code with example usage: obj._validate_parameters() without return types