class_docstr: Abstract base class for all Gaussian process models.
  
  Parameters
  ----------
  configspace : ConfigurationSpace
  kernel : Kernel
      Kernel which is used for the Gaussian process.
  instance_features : dict[str, list[int | float]] | None, defaults to None
      Features (list of int or floats) of the instances (str). The features are incorporated into the X data,
      on which the model is trained on.
  pca_components : float, defaults to 7
      Number of components to keep when using PCA to reduce dimensionality of instance features.
  seed : int
class_docstr_tok: ["Abstract","base","class","for","all","Gaussian","process","models",".","Parameters","--","--","--","--","--","configspace",":","ConfigurationSpace","kernel",":","Kernel","Kernel","which","is","used","for","the","Gaussian","process",".","instance_features",":","dict","[","str",",","list","[","int","|","float","]","]","|","None",",","defaults","to","None","Features","(","list","of","int","or","floats",")","of","the","instances","(","str",")",".","The","features","are","incorporated","into","the","X","data",",","on","which","the","model","is","trained","on",".","pca_components",":","float",",","defaults","to","7","Number","of","components","to","keep","when","using","PCA","to","reduce","dimensionality","of","instance","features",".","seed",":","int"]
docstr: Generates a Gaussian process.
docstr_tok: ["Generates","a","Gaussian","process","."]
code: def _get_gaussian_process(self) -> GaussianProcessRegressor:
      """Generates a Gaussian process."""
      raise NotImplementedError()
  
imports: from __future__ import annotations
  from abc import abstractmethod
  from typing import Any
  import numpy
  import sklearn.gaussian_process
  from ConfigSpace import ConfigurationSpace
  from sklearn.gaussian_process import GaussianProcessRegressor
  from sklearn.gaussian_process.kernels import Kernel, KernelOperator
  from smac.model.abstract_model import AbstractModel
  from smac.model.gaussian_process.priors.abstract_prior import AbstractPrior
  from smac.model.gaussian_process.priors.tophat_prior import SoftTopHatPrior, TophatPrior
label_desc: Use image node_id 3 for calling the AbstractGaussianProcess obj's underlying member method code with example usage: obj._get_gaussian_process() without return types