pla applied

algorithm/pla/perceptron_learning_algorithm.py

@@ -49,7 +49,7 @@ def train_pocket(perceptron: Perceptron, training_data: list, max_iterations: in
                 wrong_classifications.append((features, correct_class, result))
 
         # Wir sind alle Testdaten durchlaufen und haben eine minimale Fehlerrate?
-        # --> Wir merken uns die Gewichte
+        # → Wir merken uns die Gewichte
         if len(wrong_classifications) > min_false_classifications:
             min_false_classifications = len(wrong_classifications)
             best_weights = perceptron.weights

config.py

 class Config:
-    #Fabian token = "BdBSjg82_BieH-u4zDW7au4ltQjJ7C3sJ0UnfN6amiAex1Y5beDRa9AFsVjGSig25OWXGPAsmYnzEe10C-o4seuOaOJnjkW_Kh_ewQKDuIywlgtzduJr7GFgwlBI13qu"
-    token = "LUrRQZ5gRZDjek3I6mQKNx565pxcJ0Er2npYOksi0Dj3hkmVdoQbgThUkC5Q8do6S91vj5gFOY4hq1ydOe-AZCNruWJ69h7w5WBaUcRsIgEyxytTzpuZ5iKI6CCuHSvJ"
+    #Fabian
+    token = "BdBSjg82_BieH-u4zDW7au4ltQjJ7C3sJ0UnfN6amiAex1Y5beDRa9AFsVjGSig25OWXGPAsmYnzEe10C-o4seuOaOJnjkW_Kh_ewQKDuIywlgtzduJr7GFgwlBI13qu"
+    # token = "LUrRQZ5gRZDjek3I6mQKNx565pxcJ0Er2npYOksi0Dj3hkmVdoQbgThUkC5Q8do6S91vj5gFOY4hq1ydOe-AZCNruWJ69h7w5WBaUcRsIgEyxytTzpuZ5iKI6CCuHSvJ"
     host = "https://iul.fh-muenster.de/api"