class_docstr: Integrated Expected improvement acquisition function
  
  :param model: GPyOpt class of model
  :param space: GPyOpt class of domain
  :param optimizer: optimizer of the acquisition. Should be a GPyOpt optimizer
  :param cost_withGradients: function
  :param jitter: positive value to make the acquisition more explorative
  
  .. Note:: allows to compute the Improvement per unit of cost
docstr: Integrated Expected Improvement
docstr_tok: ["Integrated","Expected","Improvement"]
code: def _compute_acq(self, x):
      """
      Integrated Expected Improvement
      """
      means, stds = self.model.predict(x)
      fmins = self.model.get_fmin()
      f_acqu = 0
      for m, s, fmin in zip(means, stds, fmins):
          phi, Phi, _ = get_quantiles(self.jitter, fmin, m, s)
          f_acqu += (fmin - m + self.jitter) * Phi + s * phi
      return f_acqu / (len(means))
  
imports: from .EI import AcquisitionEI
  from ..util.general import get_quantiles
label_desc: Use image node_id 2 for calling the AcquisitionEI_MCMC obj's underlying member method code with example usage: obj._compute_acq(x) and returns: unknown