Question about function plot_decision_boundary() in 02_neural_network_classification

[1337thomas]

Hi,
I have a question about the function plot_decision_boundary(). It is the same as in the course but I have a different output for the plot

what could be the reason? My function:

def plot_decision_boundary(model, X, y):
  """
  Plots the decision boundary created by a model predicting on X
  """

  # Define the axis boundaries of the plot and create a meshgrid
  x_min, x_max = X[:, 0].min() - 0.1, X[:, 0].max() + 0.1
  y_min, y_max = X[:, 1].min() - 0.1, X[:, 1].max() + 0.1
  xx, yy = np.meshgrid(np.linspace(x_min, x_max, 100),
                       np.linspace(y_min, y_max, 100))
  
 
 # Create X value (we're going to make predictions on these)
  x_in = np.c_[xx.ravel(), yy.ravel()]

 # Make predictions
  y_pred = model.predict(x_in)

  # Check for multi-class
  if len(y_pred[0]) > 1:
    print("doing multiclass classification")
    # We have to reshape our prediction to get them ready for plotting
    y_pred = np.argmax(y_pred, axis=1).reshape(xx.shape)

  else:
    print("doing binary classification")
    y_pred = np.round(np.max(y_pred, axis=1)).reshape(xx.shape)

  # Plot the decision boundary
  plt.contourf(xx, yy, y_pred, cmap=plt.cm.RdYlBu, alpha=0.7)
  plt.scatter(X[:, 0], X[:, 1], c=y, s=40, cmap=plt.cm.RdYlBu)
  plt.xlim(xx.min(), xx.max())
  plt.ylim(yy.min(), yy.max())

what did I do wrong?