code: def __init__(self, kernel=None):
      if kernel is None:
          kernel = gaussian_process.kernels.Matern(nu=2.5)
      self.gp = gaussian_process.GaussianProcessRegressor(
          kernel=kernel,
          alpha=1e-6,
          normalize_y=True,
          n_restarts_optimizer=10,
      )
  
imports: import random
  import os
  import sys
  import collections
  import itertools
  import pickle
  import scipy.sparse
  import networkx
  import numpy
  from sklearn.cluster import SpectralClustering
  from sklearn import gaussian_process
  from scipy.optimize import minimize
  from bayes_opt import BayesianOptimization
label_desc: Use image node_id 1 to create a new GaussianProcessRegressor object from inherited base classes: object with example: obj = GaussianProcessRegressor(kernel)