diff --git a/analytics/anomaly_model.py b/analytics/anomaly_model.py
index a42de7f..f2f38d8 100644
--- a/analytics/anomaly_model.py
+++ b/analytics/anomaly_model.py
@@ -76,7 +76,7 @@ class AnomalyModel:
         self.model = self.create_algorithm()
         self.model.fit(train_augmented, confidence)
         if len(anomalies) > 0:
-            last_dataframe_time = dataframe.iloc[- 1]['timestamp']
+            last_dataframe_time = dataframe.iloc[-1]['timestamp']
             last_prediction_time = int(last_dataframe_time.timestamp() * 1000)
         else:
             last_prediction_time = 0
diff --git a/analytics/step_detector.py b/analytics/step_detector.py
index 90d761a..d2ce685 100644
--- a/analytics/step_detector.py
+++ b/analytics/step_detector.py
@@ -138,7 +138,7 @@ class StepDetector:
         self.__optimize_threshold(data, self.window_size, segments, contamination)
 
     def __optimize_threshold(self, data, window_size, segments, contamination):
-        step_size = 3
+        step_size = window_size // 2
         pattern = np.concatenate([[-1] * step_size, [1] * step_size])
         corr_res = np.correlate(data, pattern, mode='same') / window_size
         corr_res = np.concatenate((np.zeros(step_size), corr_res, np.zeros(step_size)))