Comments

app.py

@@ -13,15 +13,14 @@ from sklearn.metrics.pairwise import cosine_similarity
 from sklearn.preprocessing import LabelEncoder
 from sklearn.preprocessing import OneHotEncoder
 
-
-
-def greet_o(name, str2):
-    return "Hello " + name + "!!" + " str2=" + str2
+# TODO: Implement MBTI features
 
 def greet(name, body_profile_type):
     user_df = {}
 
     # Get user input for numerical columns
+    # TODO: Add more modifiable parameters
+
     user_df['age'] = 22.0
     user_df['status'] = 1.0
     user_df['sex'] = 0.0
@@ -60,6 +59,10 @@ def greet(name, body_profile_type):
     #return "Hello " + name + "!!" + " str2=" + str2
     return suggested_name
 
+def greet_test(name, str2):
+    return "Hello " + name + "!!" + " str2=" + str2
+
+# Bootstrap the model
 # reading dataset using panda
 tinder_df = pd.read_csv("tinder_data.csv")