plotting prediction and residuals

visualization

    # plotting after prediction
    xa = np.array(x.x) # column name of x is x 
    order = np.argsort(xa)
    xs = np.array(xa)[order]
    ys = np.array(predf)[order]
    
    #epreds = np.array(epred[:,None])[order]

    f, (ax1, ax2) = plt.subplots(1, 2, sharey=True, figsize = (13,2.5))

    ax1.plot(x,y, 'o')
    ax1.plot(xs, ys, 'r')
    ax1.set_title(f'Prediction (Iteration {i+1})')
    ax1.set_xlabel('x')
    ax1.set_ylabel('y / y_pred')

    ax2.plot(x, ei, 'go')
    ax2.set_title(f'Residuals vs. x (Iteration {i+1})')
    ax2.set_xlabel('x')
    ax2.set_ylabel('Residuals')