code: def test_invalid_estimator():
      expect = "Estimator must have an ._estimator_type for infering `scoring`"
      assert_raises(AttributeError, expect, SFS, PCA())
  
      class PCA2(PCA):
          def __init__(self):
              super().__init__()
              self._estimator_type = "something"
  
      expect = "Estimator must be a Classifier or Regressor."
      assert_raises(AttributeError, expect, SFS, PCA2())
  
imports: import numpy
  import pandas
  from numpy import nan
  from numpy.testing import assert_almost_equal
  from packaging.version import Version
  from sklearn import __version__
  from sklearn.datasets import load_iris
  from sklearn.decomposition import PCA
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LinearRegression
  from sklearn.metrics import accuracy_score, make_scorer, roc_auc_score
  from sklearn.model_selection import GridSearchCV, GroupKFold
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.pipeline import Pipeline
  from mlxtend.classifier import SoftmaxRegression
  from mlxtend.data import boston_housing_data
  from mlxtend.feature_selection import SequentialFeatureSelector
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 42 for calling a global function with example usage: test_invalid_estimator() without return types