MAINT make plot_digits_denoising deterministic by fixing random state (scikit-learn#26004)

mdarii · Itay · commit c1a2106b74f6 · 2023-04-15T23:06:52.000+03:00
diff --git a/examples/applications/plot_cyclical_feature_engineering.py b/examples/applications/plot_cyclical_feature_engineering.py
@@ -216,6 +216,7 @@
     ),
     HistGradientBoostingRegressor(
         categorical_features=categorical_columns,
+        random_state=42,
     ),
 ).set_output(transform="pandas")
 
diff --git a/examples/applications/plot_digits_denoising.py b/examples/applications/plot_digits_denoising.py
@@ -98,9 +98,14 @@ def plot_digits(X, title):
 # uses a radial basis function (RBF) kernel.
 from sklearn.decomposition import PCA, KernelPCA
 
-pca = PCA(n_components=32)
+pca = PCA(n_components=32, random_state=42)
 kernel_pca = KernelPCA(
-    n_components=400, kernel="rbf", gamma=1e-3, fit_inverse_transform=True, alpha=5e-3
+    n_components=400,
+    kernel="rbf",
+    gamma=1e-3,
+    fit_inverse_transform=True,
+    alpha=5e-3,
+    random_state=42,
 )
 
 pca.fit(X_train_noisy)
