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).
class_docstr_tok: ["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",")","."]
docstr: Array of local positions.
docstr_tok: ["Array","of","local","positions","."]
code: def local_position(self) -> np.ndarray:
      """Array of local positions."""
  
      return self._local_position
  
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 6 for calling the SSD obj's underlying member method code with example usage: obj.local_position() and returns: self