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# dennybritz/plot_decision_boundary.py Created Sep 18, 2015

plot_decision_boundary.py
 # Helper function to plot a decision boundary. # If you don't fully understand this function don't worry, it just generates the contour plot below. def plot_decision_boundary(pred_func): # Set min and max values and give it some padding x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5 y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5 h = 0.01 # Generate a grid of points with distance h between them xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h)) # Predict the function value for the whole gid Z = pred_func(np.c_[xx.ravel(), yy.ravel()]) Z = Z.reshape(xx.shape) # Plot the contour and training examples plt.contourf(xx, yy, Z, cmap=plt.cm.Spectral) plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Spectral)

### LRDPRDX commented Mar 3, 2017

 There is error because of the last line: Unexpected indent.

### hack-r commented Aug 25, 2017

 @BogdanBessit The error is in how you pasted his code, not in the function...

### duhaime commented Dec 21, 2017

 This code comes more or less from the Scikit docs, e.g. in their example of a KNN classifier

### DiWuDi commented Oct 1, 2018

 Just click the "raw" on the top right corner, and copy from there. Then past it to your Jupyter cell.