Add error handling at model choice

src/processing.py

@@ -22,6 +22,14 @@ def choose_model(model):
         return DecisionTreeClassifier(random_state=42)
     elif model == "neuralnet":
         return MLPClassifier(hidden_layer_sizes=10)
+    else:
+        print("Unknown model selected. The choices are: ")
+        print("gnb: Gaussian Naive Bayes")
+        print("svc: Linear Support Vector Classification")
+        print("knn: K-neighbors")
+        print("tree: Decision tree")
+        print("neuralnet: MLP Classifier")
+        exit()
 
 
 def predict_data(data, target, model):