code: def plot_hyperplane(clf, min_x, max_x, linestyle, label):
      # get the separating hyperplane
      w = clf.coef_[0]
      a = -w[0] / w[1]
      xx = np.linspace(
          min_x - 5, max_x + 5
      )  # make sure the line is long enough
      yy = a * xx - (clf.intercept_[0]) / w[1]
      plt.plot(xx, yy, linestyle, label=label)
  
file_path: scikit-learn/examples/miscellaneous/plot_multilabel.py
imports: import matplotlib.pyplot
  import numpy
  from sklearn.cross_decomposition import CCA
  from sklearn.datasets import make_multilabel_classification
  from sklearn.decomposition import PCA
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.svm import SVC
label_desc: Use image node_id 1 for calling a global function with example usage: plot_hyperplane(clf, min_x, max_x, linestyle, label) without return types