class_docstr: An SSD class, inherited from Optimizer.
  
  This is the designed class to define SSD-related
  variables and methods.
  
  References:
      A. Tharwat and T. Gabel.
      Parameters optimization of support vector machines for imbalanced data using social ski driver algorithm.
      Neural Computing and Applications (2019).
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docstr: Calculates the mean global solution (eq. 9).
  
  Args:
      alpha: 1st agent's current position.
      beta: 2nd agent's current position.
      gamma: 3rd agent's current position.
  
  Returns:
      (np.ndarray): Mean global solution.
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code: def _mean_global_solution(
      self, alpha: np.ndarray, beta: np.ndarray, gamma: np.ndarray
  ) -> np.ndarray:
      """Calculates the mean global solution (eq. 9).
  
      Args:
          alpha: 1st agent's current position.
          beta: 2nd agent's current position.
          gamma: 3rd agent's current position.
  
      Returns:
          (np.ndarray): Mean global solution.
  
      """
  
      mean = (alpha + beta + gamma) / 3
  
      return mean
  
imports: import copy
  import time
  from typing import Any, Dict, Optional
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.exception
  from opytimizer.core import Optimizer
  from opytimizer.core.function import Function
  from opytimizer.core.space import Space
  from opytimizer.utils import logging
label_desc: Use image node_id 11 for calling the SSD obj's underlying member method code with example usage: obj._mean_global_solution(alpha, beta, gamma) and returns: mean