Update classificator.py

classificator.py

@@ -51,6 +51,7 @@ def predict(cv, job, weight):
   major_similarity = cosine_similarity(st.encode(cv['userMajors']).reshape(1,-1), st.encode(job['majors']).reshape(1,-1))[0][0] if cv['userMajors'] != '[]' else 0
   skill_similarity = cosine_similarity(st.encode(cv['skills']).reshape(1,-1), st.encode(job['skills']).reshape(1,-1))[0][0] if cv['skills'] != '[]' else 0
   # score_yoe = 0.5 if diffYoe == -1 else (0 if diffYoe < 0 else 1)
+
   coords_1 = get_coordinates(cv['location'])
   coords_2 = get_coordinates(job['location'])
   distance = 999999
@@ -60,7 +61,7 @@ def predict(cv, job, weight):
   else:
       raise ValueError("Could not get coordinates for one or both cities.")
 
-  score = weight['exp'] * role_req_exp + weight['position'] * role_pos  + weight['major'] * major_similarity + weight['diffYoe']* diffYoe + weight['skills'] * skill_similarity + weight['location'] * (1 / (1 + distance))
+  score = weight['exp'] * role_req_exp + weight['position'] * role_pos  + weight['major'] * major_similarity + weight['diffYoe']* diffYoe/job['minYoE'] + weight['skills'] * skill_similarity + weight['location'] * (1 / (1 + distance))
   # data = [{
   #   'role_req-exp': role_req_exp,      
   #   'role_pos': role_pos,