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classificator.py

@@ -35,7 +35,7 @@ def predict(cv, job):
   role_pos = cosine_similarity(st.encode(cv['positions']).reshape(1,-1), st.encode(job['role']).reshape(1,-1))[0][0]
   major_similarity = cosine_similarity(st.encode(cv['userMajors']).reshape(1,-1), st.encode(job['majors']).reshape(1,-1))[0][0]
   skill_similarity = cosine_similarity(st.encode(cv['skills']).reshape(1,-1), st.encode(job['skills']).reshape(1,-1))[0][0]
-  score_yoe = 0.5 if diffYoe == -1 else (1 if diffYoe > 0 else 0)
+  score_yoe = 0.5 if diffYoe == -1 else (0 if diffYoe < 0 else 1)
   score = 0.35 * role_req_exp + 0.1 * role_pos  + 0.15 * major_similarity + 0.3* score_yoe + 0.1 * skill_similarity 
   X = np.array([role_req_exp, role_pos, major_similarity, skill_similarity, score]).reshape(1, -1)
   res = model.predict(X)