code: def _get_hyperbolic_dataset(self, intrinsic=True):
      X_train = gs.array(
          [
              [1 / 2, 1 / 4],
              [1 / 2, 0],
              [1 / 2, -1 / 4],
              [-1 / 2, 1 / 4],
              [-1 / 2, 0],
              [-1 / 2, -1 / 4],
          ]
      )
      if not intrinsic:
          X_train = _Hyperbolic.change_coordinates_system(
              X_train,
              from_coordinates_system="intrinsic",
              to_coordinates_system="extrinsic",
          )
  
      return X_train, gs.array([0, 0, 0, 1, 1, 1])
  
file_path: geomstats/tests/tests_geomstats/test_learning/data/kernel_density_estimation_classifier.py
imports: import geomstats.backend
  from geomstats.geometry._hyperbolic import _Hyperbolic
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.hyperboloid import Hyperboloid
  from geomstats.geometry.hypersphere import Hypersphere
  from geomstats.geometry.poincare_ball import PoincareBall
  from geomstats.learning.kernel_density_estimation_classifier import KernelDensityEstimationClassifier
  from geomstats.learning.radial_kernel_functions import triangular_radial_kernel
  from geomstats.test.data import TestData
label_desc: Use image node_id 3 for calling the KernelDensityEstimationClassifierTestData obj's underlying member method code with example usage: obj._get_hyperbolic_dataset(intrinsic) and returns: X_train,  gs