code: def test_valid_but_unsupported_language():
      dataset = load_iris()
      x, y = dataset.data, dataset.target
      clf = AdaBoostClassifier()
      clf.fit(X=x, y=y)
      with pytest.raises(exception.NotSupportedYetError):
          Estimator(clf, language="ruby")
  
imports: import os
  import random
  import shutil
  import warnings
  from os import environ
  from pathlib import Path
  from sys import version_info
  from typing import Callable, Tuple
  import numpy
  import pytest
  from joblib import dump
  from sklearn import preprocessing
  from sklearn.base import BaseEstimator
  from sklearn.datasets import load_iris
  from sklearn.ensemble.forest import ExtraTreesClassifier, RandomForestClassifier
  from sklearn.ensemble.weight_boosting import AdaBoostClassifier
  from sklearn.linear_model import SGDClassifier
  from sklearn.naive_bayes import BernoulliNB, GaussianNB
  from sklearn.neighbors.classification import KNeighborsClassifier
  from sklearn.svm import SVC, LinearSVC, NuSVC
  from sklearn.tree.tree import DecisionTreeClassifier
  from sklearn_porter import exceptions
  from sklearn_porter.cli.__main__ import parse_args
  from sklearn_porter.Estimator import Estimator, can, show
  from sklearn_porter.cli.command.port import main
  from sklearn_porter.cli.command.save import main
  from sklearn_porter.cli.command.show import main
  from tests.commons import SKLEARN_VERSION, CANDIDATES, CLASSIFIERS, DATASETS, Candidate, Dataset, ROOT_DIR, RESOURCES_DIR
  from tests.utils import dataset_generate_x, dataset_uniform_x, fs_mkdir
label_desc: Use image node_id 6 for calling a global function with example usage: test_valid_but_unsupported_language() without return types