DOC: use notebook-style for plot_svm_regression.py example (scikit-learn#22534)

jayasuryajsk · lesteve · thomasjpfan · commit 23a09e92dd81 · 2022-03-01T13:57:33.000-05:00
Co-authored-by: Loïc Estève &lt;loic.esteve@ymail.com&gt;
diff --git a/examples/svm/plot_svm_regression.py b/examples/svm/plot_svm_regression.py
@@ -11,23 +11,25 @@
 from sklearn.svm import SVR
 import matplotlib.pyplot as plt
 
-# #############################################################################
+# %%
 # Generate sample data
+# --------------------
 X = np.sort(5 * np.random.rand(40, 1), axis=0)
 y = np.sin(X).ravel()
 
-# #############################################################################
-# Add noise to targets
+# add noise to targets
 y[::5] += 3 * (0.5 - np.random.rand(8))
 
-# #############################################################################
+# %%
 # Fit regression model
+# --------------------
 svr_rbf = SVR(kernel="rbf", C=100, gamma=0.1, epsilon=0.1)
 svr_lin = SVR(kernel="linear", C=100, gamma="auto")
 svr_poly = SVR(kernel="poly", C=100, gamma="auto", degree=3, epsilon=0.1, coef0=1)
 
-# #############################################################################
+# %%
 # Look at the results
+# -------------------
 lw = 2
 
 svrs = [svr_rbf, svr_lin, svr_poly]
