Add types to remaining files; activate mypy's disallow_untyped_defs

tests/classifiers/test_counting.py

@@ -10,7 +10,7 @@ from miplearn.classifiers.counting import CountingClassifier
 E = 0.1
 
 
-def test_counting():
+def test_counting() -> None:
     clf = CountingClassifier()
     n_features = 25
     x_train = np.zeros((8, n_features))

tests/classifiers/test_sklearn.py

@@ -10,7 +10,7 @@ from sklearn.neighbors import KNeighborsClassifier
 from miplearn.classifiers.sklearn import ScikitLearnClassifier, ScikitLearnRegressor
 
 
-def test_constant_prediction():
+def test_constant_prediction() -> None:
     x_train = np.array([[0.0, 1.0], [1.0, 0.0]])
     y_train = np.array([[True, False], [True, False]])
     clf = ScikitLearnClassifier(KNeighborsClassifier(n_neighbors=1))
@@ -22,7 +22,7 @@ def test_constant_prediction():
     )
 
 
-def test_regressor():
+def test_regressor() -> None:
     x_train = np.array([[0.0, 1.0], [1.0, 4.0], [2.0, 2.0]])
     y_train = np.array([[1.0], [5.0], [4.0]])
     x_test = np.array([[4.0, 4.0], [0.0, 0.0]])

tests/classifiers/test_threshold.py

@@ -10,7 +10,7 @@ from miplearn.classifiers import Classifier
 from miplearn.classifiers.threshold import MinPrecisionThreshold
 
 
-def test_threshold_dynamic():
+def test_threshold_dynamic() -> None:
     clf = Mock(spec=Classifier)
     clf.predict_proba = Mock(
         return_value=np.array(