code: def _svm(opytimizer):
      # Gathers params
      C = opytimizer[0][0]
  
      # Instanciating an SVC class
      svc = svm.SVC(C=C, kernel="linear")
  
      # Creates a cross-validation holder
      k_fold = KFold(n_splits=5)
  
      # Fitting model using cross-validation
      scores = cross_val_score(svc, X, Y, cv=k_fold, n_jobs=-1)
  
      # Calculates scores mean
      mean_score = np.mean(scores)
  
      return 1 - mean_score
  
file_path: opytimizer/examples/integrations/sklearn/svm.py
imports: import numpy
  from sklearn import svm
  from sklearn.datasets import load_digits
  from sklearn.model_selection import KFold, cross_val_score
  from opytimizer import Opytimizer
  from opytimizer.core import Function
  from opytimizer.optimizers.swarm import PSO
  from opytimizer.spaces import SearchSpace
label_desc: Use image node_id 1 for calling a global function with example usage: _svm(opytimizer) and returns: unknown