code: def make_dataset(n_samples):
      X, y = make_classification(
          n_samples=n_samples,
          n_features=2,
          n_informative=2,
          n_redundant=0,
          random_state=0,
      )
      return train_test_split(X, y, test_size=0.33, random_state=0)
  
imports: import matplotlib.pyplot
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  from sklearn.linear_model import LogisticRegression
  from sklearn_evaluation import plot
label_desc: Use image node_id 1 for calling a global function with example usage: make_dataset(n_samples) and returns: train_test_split