code: def test_knn_option_sffs():
      iris = load_iris()
      X = iris.data
      y = iris.target
      knn = KNeighborsClassifier(n_neighbors=4)
      sfs2 = SFS(
          knn,
          k_features=3,
          forward=True,
          floating=True,
          cv=4,
          verbose=0,
      )
      sfs2 = sfs2.fit(X, y)
      assert sfs2.k_feature_idx_ == (1, 2, 3)
  
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 15 for calling a global function with example usage: test_knn_option_sffs() without return types