class_docstr: Check various non-sklearn estimators to see if the wrapper works for them
class_docstr_tok: ["Check","various","non-sklearn","estimators","to","see","if","the","wrapper","works","for","them"]
docstr: Validate cuML classifier with wrapper
docstr_tok: ["Validate","cuML","classifier","with","wrapper"]
code: def test_cuml_classifier(self):
      """
      Validate cuML classifier with wrapper
      """
      # NOTE: this is currently untested as I wasn't able to install cuML
      X, y = make_classification(
          n_samples=400,
          n_features=10,
          n_informative=2,
          n_redundant=3,
          n_classes=2,
          n_clusters_per_class=2,
          random_state=8311982,
      )
      X_train, X_test, y_train, y_test = tts(X, y)
  
      # Convert to cudf dataframes
      X_train = cudf.DataFrame(X_train)
      y_train = cudf.Series(y_train)
      X_test = cudf.DataFrame(X_test)
      y_test = cudf.Series(y_test)
  
      model = classifier(
          curfc(n_estimators=40, max_depth=8, max_features=1)
      )
      oz = classification_report(
          model, X_train, y_train, X_test, y_test, show=False
      )
      assert is_fitted(oz)
  
imports: import pytest
  from yellowbrick.contrib.wrapper import *
  from yellowbrick.regressor import residuals_plot
  from yellowbrick.classifier import classification_report
  from yellowbrick.exceptions import YellowbrickAttributeError
  from yellowbrick.utils.helpers import get_model_name, is_fitted
  from yellowbrick.utils.types import is_estimator, is_probabilistic
  from yellowbrick.utils.types import is_classifier, is_clusterer, is_regressor
  from sklearn.base import is_regressor
  from sklearn.base import is_classifier
  from sklearn.model_selection import train_test_split
  from sklearn.datasets import make_classification, make_regression
  from sklearn.base import is_outlier_detector
label_desc: Use image node_id 3 for calling the TestNonSklearnEstimators obj's underlying member method code with example usage: obj.test_cuml_classifier() without return types