class_docstr: Gaussian process regressor.
  Attributes:
      alpha: A hyperparameter.
class_docstr_tok: ["Gaussian","process","regressor",".","Attributes",":","alpha",":","A","hyperparameter","."]
docstr: if it is firsr fitted
          
docstr_tok: ["if","it","is","firsr","fitted"]
code: def first_fitted(self):
      """if it is firsr fitted"""
      return self._first_fitted
  
imports: import math
  import random
  from copy import deepcopy
  from functools import total_ordering
  from queue import PriorityQueue
  import numpy
  from scipy.linalg import LinAlgError, cho_solve, cholesky, solve_triangular
  from scipy.optimize import linear_sum_assignment
  from sklearn.metrics.pairwise import rbf_kernel
  from nni.utils import OptimizeMode
  from .graph_transformer import transform
  from .utils import Constant
  from .layers import is_layer
label_desc: Use image node_id 5 for calling the IncrementalGaussianProcess obj's underlying member method code with example usage: obj.first_fitted() and returns: self