diff --git a/sklearn/cluster/_hdbscan/hdbscan.py b/sklearn/cluster/_hdbscan/hdbscan.py
index 3d8ec08ac3..f1584f46d6 100644
--- a/sklearn/cluster/_hdbscan/hdbscan.py
+++ b/sklearn/cluster/_hdbscan/hdbscan.py
@@ -62,7 +62,7 @@ FAST_METRICS = set(KDTree.valid_metrics() + BallTree.valid_metrics())
 # Encodings are arbitrary but must be strictly negative.
 # The current encodings are chosen as extensions to the -1 noise label.
 # Avoided enums so that the end user only deals with simple labels.
-_OUTLIER_ENCODING = {
+_OUTLIER_ENCODING: dict = {
     "infinite": {
         "label": -2,
         # The probability could also be 1, since infinite points are certainly
diff --git a/sklearn/cluster/tests/test_hdbscan.py b/sklearn/cluster/tests/test_hdbscan.py
index c21b188fd5..b652a99aa2 100644
--- a/sklearn/cluster/tests/test_hdbscan.py
+++ b/sklearn/cluster/tests/test_hdbscan.py
@@ -34,9 +34,7 @@ ALGORITHMS = [
     "auto",
 ]
 
-OUTLIER_SET = {-1} | {
-    out["label"] for _, out in _OUTLIER_ENCODING.items()  # type: ignore
-}
+OUTLIER_SET = {-1} | {out["label"] for _, out in _OUTLIER_ENCODING.items()}
 
 
 @pytest.mark.parametrize("outlier_type", _OUTLIER_ENCODING)
diff --git a/sklearn/tests/test_metaestimators_metadata_routing.py b/sklearn/tests/test_metaestimators_metadata_routing.py
index 1cd21ae817..5160a4b46b 100644
--- a/sklearn/tests/test_metaestimators_metadata_routing.py
+++ b/sklearn/tests/test_metaestimators_metadata_routing.py
@@ -171,7 +171,7 @@ class ConsumingClassifier(ClassifierMixin, BaseEstimator):
         # return np.zeros(shape=(len(X), 2))
 
 
-METAESTIMATORS = [
+METAESTIMATORS: list = [
     {
         "metaestimator": MultiOutputRegressor,
         "estimator_name": "estimator",
@@ -232,9 +232,7 @@ The keys are as follows:
 """
 
 # ids used for pytest fixture
-METAESTIMATOR_IDS = [
-    str(row["metaestimator"].__name__) for row in METAESTIMATORS  # type: ignore
-]
+METAESTIMATOR_IDS = [str(row["metaestimator"].__name__) for row in METAESTIMATORS]
 
 
 def test_registry_copy():