class_docstr: Base class for density estimation and regression KDE classes.
class_docstr_tok: ["Base","class","for","density","estimation","and","regression","KDE","classes","."]
docstr: Sets the default values for the efficient estimation
docstr_tok: ["Sets","the","default","values","for","the","efficient","estimation"]
code: def _set_defaults(self, defaults):
      """Sets the default values for the efficient estimation"""
      self.n_res = defaults.n_res
      self.n_sub = defaults.n_sub
      self.randomize = defaults.randomize
      self.return_median = defaults.return_median
      self.efficient = defaults.efficient
      self.return_only_bw = defaults.return_only_bw
      self.n_jobs = defaults.n_jobs
  
imports: import copy
  import numpy
  from scipy import optimize
  from scipy.stats.mstats import mquantiles
  from .None import kernels
label_desc: Use image node_id 5 for calling the GenericKDE obj's underlying member method code with example usage: obj._set_defaults(defaults) without return types