diff --git a/frontend/normstrategy.py b/frontend/normstrategy.py
index af4dde3..5a50bab 100644
--- a/frontend/normstrategy.py
+++ b/frontend/normstrategy.py
@@ -130,6 +130,10 @@ class KNNStrategy(MVStrategy):
         df.fillna(usable_data, inplace=True)
         return df
 
+    def count_max(self, df: DataFrame, label: str) -> int:
+        usable_data = df.dropna(subset=self.training_features)
+        return usable_data[label].count()
+
     def __str__(self) -> str:
         return "kNN"
 
diff --git a/frontend/pages/normalization.py b/frontend/pages/normalization.py
index b543f87..34de383 100644
--- a/frontend/pages/normalization.py
+++ b/frontend/pages/normalization.py
@@ -16,9 +16,8 @@ if "data" in st.session_state:
             key=f"mv-{column}",
         )
         if isinstance(option, KNNStrategy):
-            print(option.available_features)
             option.training_features = st.multiselect("Training columns", option.training_features, default=option.available_features, key=f"cols-{column}")
-            option.n_neighbors = st.number_input("Number of neighbors", min_value=1, value=option.n_neighbors, key=f"neighbors-{column}")
+            option.n_neighbors = st.number_input("Number of neighbors", min_value=1, max_value=option.count_max(data, column), value=option.n_neighbors, key=f"neighbors-{column}")
         # Always re-get the series to avoid reusing an invalidated series pointer
         data = option.apply(data, column, data[column])