new_contents: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  import numpy as np
  from sklearn import svm
  
  """
  use self defined kernel function
  not understand very clearly, but it works
  """
  
  def my_kernel(x, y):
      xx = pow(-1, x)
      yy = pow(-1, y)
      return xx @ yy.T
  
  x = [[i] for i in range(10)]
  y = [ i%2 for i in range(10)]
  s = svm.SVC(kernel = my_kernel)
  #s = svm.SVC()
  s.fit(x, y)
  
  yy = [ s.predict([[i]]) for i in range(2000)]
  yy = [i[0] for i in yy]
  
  yy_correct = [ i%2 for i in range(2000)]
  
  nu_error = 0
  
  for i in range(len(yy)):
      if yy[i] != yy_correct[i]:
          nu_error = nu_error + 1
  
  print(nu_error)
  
  print(s.predict([[i] for i in range(10000, 10010)]))
  
subject: add sklean