Make HDDM drift detectors report downward changes (online-ml#575)

* Make HDDM_A properly report downward drift with two_sided_test * Make HDDM_W report concept drift during downward changes when two_sided_test is set to True * Fix downward warning zone in HDDM_W * Fix downward warning zone in HDDM_W
praveenjoshi01 · Aug 17, 2021 · 8ef9774 · 8ef9774
1 parent 32aadd0
commit 8ef9774
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Showing 2 changed files with 22 additions and 11 deletions.
diff --git a/river/drift/hddm_a.py b/river/drift/hddm_a.py
@@ -132,13 +132,19 @@ def update(self, value) -> tuple:
             self._in_concept_change = False
             self._in_warning_zone = False
 
-        if self.two_sided_test and self._mean_decr(
-            self.c_max, self.n_max, self.total_c, self.total_n
-        ):
-            self.n_estimation = self.total_n - self.n_max
-            self.c_estimation = self.total_c - self.c_max
-            self.n_min = self.n_max = self.total_n = 0
-            self.c_min = self.c_max = self.total_c = 0
+        if self.two_sided_test:
+            if self._mean_decr(
+                self.c_max, self.n_max, self.total_c, self.total_n, self.drift_confidence
+            ):
+                self.n_estimation = self.total_n - self.n_max
+                self.c_estimation = self.total_c - self.c_max
+                self.n_min = self.n_max = self.total_n = 0
+                self.c_min = self.c_max = self.total_c = 0
+                self._in_concept_change = True
+            elif self._mean_decr(
+                self.c_max, self.n_max, self.total_c, self.total_n, self.warning_confidence
+            ):
+                self._in_warning_zone = True
 
         self._update_estimations()
 
@@ -153,12 +159,12 @@ def _mean_incr(c_min, n_min, total_c, total_n, confidence):
         cota = sqrt(m / 2 * log(2.0 / confidence))
         return total_c / total_n - c_min / n_min >= cota
 
-    def _mean_decr(self, c_max, n_max, total_c, total_n):
+    def _mean_decr(self, c_max, n_max, total_c, total_n, confidence):
         if n_max == total_n:
             return False
 
         m = (total_n - n_max) / n_max * (1.0 / total_n)
-        cota = sqrt(m / 2 * log(2.0 / self.drift_confidence))
+        cota = sqrt(m / 2 * log(2.0 / confidence))
         return c_max / n_max - total_c / total_n >= cota
 
     def reset(self):

diff --git a/river/drift/hddm_w.py b/river/drift/hddm_w.py
@@ -135,8 +135,13 @@ def update(self, value):
             self._in_warning_zone = False
 
         self._update_decr_statistics(value, self.drift_confidence)
-        if self.two_sided_test and self._monitor_mean_decr(self.drift_confidence):
-            self.reset()
+        if self.two_sided_test:
+            if self._monitor_mean_decr(self.drift_confidence):
+                self.reset()
+                self._in_concept_change = True
+            elif self._monitor_mean_decr(self.warning_confidence):
+                self._in_warning_zone = True
+
         self.estimation = self.total.EWMA_estimator
 
         return self._in_concept_change, self._in_warning_zone