updating examples according to the new sklearn version

Menelau · Menelau · commit 554b0231f65e · 2024-04-11T23:29:23.000-04:00
diff --git a/examples/example_calibrating_classifiers.py b/examples/example_calibrating_classifiers.py
@@ -93,7 +93,7 @@
 # DS methods.
 calibrated_pool = []
 for clf in pool_classifiers:
-    calibrated = CalibratedClassifierCV(base_estimator=clf, cv='prefit')
+    calibrated = CalibratedClassifierCV(estimator=clf, cv='prefit')
     calibrated.fit(X_dsel, y_dsel)
     calibrated_pool.append(calibrated)
 
diff --git a/examples/plot_random_forest.py b/examples/plot_random_forest.py
@@ -43,7 +43,8 @@
 rng = np.random.RandomState(42)
 
 # Fetch a classification dataset from OpenML
-data = fetch_openml(name='credit-g', version=1, cache=False, as_frame=False)
+data = fetch_openml(name='phoneme', version=1,
+                    cache=False, as_frame=False)
 X = data.data
 y = data.target
 # split the data into training and test data
@@ -57,7 +58,7 @@
 RF.fit(X_train, y_train)
 
 X_train, X_dsel, y_train, y_dsel = train_test_split(X_train, y_train,
-                                                    test_size=0.50,
+                                                    test_size=0.750,
                                                     random_state=rng)
 
 stacked = StackedClassifier(RF, LogisticRegression())
