Mehr Printausgaben - Alle Märkte wieder einbezogen

main.py

@@ -40,6 +40,7 @@ def run_cross_validation():
                     if excluded_folder == Markt.Kein_Markt:
                         continue
                     config_knn.excluded_folder = excluded_folder
+                    print("Konfiguration KNN: " + config_knn.__str__())
                     worksheet, r, evaluate_metrics, training_duration_model = run_model(config, config_knn, worksheet, r)
                     model_evaluate_metrics.append(evaluate_metrics)
                     training_duration_models.append(training_duration_model)
@@ -48,13 +49,6 @@ def run_cross_validation():
                 print("Speichere die Excel Tabelle")
                 save_excel(workbook, config, config_knn)
 
-    # config_knn = ConfigKNN(
-    #    excluded_folder=Markt.Markt_C,
-    #    activation_function_1_units=Aktivierungsfunktion.sigmoid,
-    #    activation_function_128_units=Aktivierungsfunktion.ReLU,
-    #    optimization_method=Optimierungsverfahren.SGD
-    # )
-
 
 # run a model definition
 def run_model(config, config_knn, worksheet, r):

ressources/config/config.yaml

 bilder:
-  original_path: "assets/Bilder/Datengrundlage-Reduziert-Test/"
-  # original_path: "assets/Bilder/Datengrundlage/"
+  # original_path: "assets/Bilder/Datengrundlage-Reduziert-Test/"
+  original_path: "assets/Bilder/Datengrundlage/"
   knn_path: "assets/Bilder/AktuelleTrainingsUndTestdaten/"
 knn:
-  epochs: 2
+  epochs: 10
 result:
   plot_path: "ressources/results/plot/"
   excel_path: "ressources/results/excel/"

src/enum/marktEnum.py

@@ -4,8 +4,8 @@ from enum import Enum
 class Markt(Enum):
     Markt_A = 0,
     Markt_B = 1,
-    #Markt_C = 2,
-    #Markt_D = 3,
-    #Markt_E = 4,
-    #Markt_F = 5
+    Markt_C = 2,
+    Markt_D = 3,
+    Markt_E = 4,
+    Markt_F = 5
     Kein_Markt = -1

src/knn/configKNN.py

 from src.enum.activierungsfunktionEnum import Aktivierungsfunktion
+from src.enum.marktEnum import Markt
 from src.enum.optimierungsverfahren import Optimierungsverfahren
 
 
 class ConfigKNN:
     def __init__(self,
-                 excluded_folder=None,
+                 excluded_folder=Markt.Kein_Markt,
                  activation_function_128_units=Aktivierungsfunktion.ReLU,
-                 activation_function_1_units=Aktivierungsfunktion.ReLU,
+                 activation_function_1_units=Aktivierungsfunktion.sigmoid,
                  optimization_method=Optimierungsverfahren.SGD):
         self.excluded_folder = excluded_folder
         self.activation_function_128_units = activation_function_128_units
         self.activation_function_1_units = activation_function_1_units
         self.optimization_method = optimization_method
+
+    def __str__(self):
+        return "optimization_method: " \
+            + self.optimization_method.name + " - activation_function_128_units: " \
+            + self.activation_function_128_units.name + ' - activation_function_1_units: ' \
+            + self.activation_function_1_units.name + ' - excluded_folder: ' \
+            + self.excluded_folder.name