code: def build_dataset(
      n_samples=50, n_features=200, n_targets=1, sparse_X=False
  ):
      """Build samples and observation for linear regression problem."""
      random_state = np.random.RandomState(0)
      if n_targets > 1:
          w = random_state.randn(n_features, n_targets)
      else:
          w = random_state.randn(n_features)
  
      if sparse_X:
          X = sparse.random(
              n_samples,
              n_features,
              density=0.5,
              format="csc",
              random_state=random_state,
          )
  
      else:
          X = np.asfortranarray(
              random_state.randn(n_samples, n_features)
          )
  
      y = X.dot(w)
      return X, y
  
label_desc: Use image node_id 1 for calling a global function with example usage: build_dataset(n_samples, n_features, n_targets, sparse_X) and returns: X,  y