code: def plot_dataset(X, y, ax=None, title=None, **params):
      if ax is None:
          ax = plt.gca()
      ax.scatter(
          X[:, 0],
          X[:, 1],
          marker="o",
          c=y,
          s=25,
          edgecolor="k",
          **params,
      )
      ax.set_xlabel("Feature 1")
      ax.set_ylabel("Feature 2")
      if title is not None:
          ax.set_title(title)
      return ax
  
file_path: DESlib/examples/plot_example_P2.py
imports: import matplotlib.pyplot
  import numpy
  from sklearn.ensemble import AdaBoostClassifier, RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.neural_network import MLPClassifier
  from sklearn.svm import SVC
  from sklearn.tree import DecisionTreeClassifier
  from deslib.dcs.ola import OLA
  from deslib.dcs.rank import Rank
  from deslib.des.des_p import DESP
  from deslib.des.knora_e import KNORAE
  from deslib.static import StackedClassifier
  from deslib.util.datasets import make_P2
label_desc: Use image node_id 3 for calling a global function with example usage: plot_dataset(X, y, ax, title) and returns: ax