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    the number of diners in the cafeteria Prediction

    Algorithm | Structured | Regression | Behavioral psychology | MAE

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    Setup D-0

     

    쉽고 간단하게 public score 80점 밑으로.

    Henry_Lee
    2021.06.17 15:49 9,180 Views language
    comments 14

    아래 사항으로 추가 시도하여, 퍼블린 점수 80점 밑으로 갔어요.
    * feature x에 '일' 추가.
    * XGBoost 모델 및 GridSearch 사용.

    -
    안녕하세요? 아래 2가지 아이디어만으로도 괜찮은 점수 달성해서, 처음으로 코드공유해봅니다.
    * '휴가자', '재택근무자'를 정원에서 차감.
    * '요일'을 '석식계'  rank에 맞춰 인코딩.
    어렵기만 했던 다른 대회와 달리, 이번 대회는 이것저것 생각하고 시도해볼 수 있어 좋습니다.
    다들 포기하지 마시고, 끝까지 화이팅해요!

    Code
    14 Comments
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    함께하는우리
    2021.06.28 14:51

    요즘 LGBM이나 catboost 많이 써서 한번 사용해보시는거 추천드립니다 ~ ㅎㅎ

    Henry_Lee
    2021.06.29 14:54

    네, 감사합니다! ㅎㅎㅎ

    와퍼세트
    2021.06.30 16:50

    6차 시도 해보셨나요? 점수가 올랐나요?

    Henry_Lee
    2021.07.01 10:13

    해봤는데, 오히려 점수가 떨어졌습니다. ㅠ
    다시 접근해봐야겠어요..;;

    nu.csu
    2021.07.02 14:35

    식사가능자수 구하실 때 출장자 수는 뺀 이유가 있나요?

    Henry_Lee
    2021.07.02 19:49

    휴가자, 재택근무자와는 달리 사무실에 체류할 가능성이 있다고 판단한 접근이었습니다.
    예를 들어, '출장을 13시에 나간다면, 밥을 먹고 가지 않을까?' 하는 것이죠.

    nu.csu
    2021.07.05 10:22

    넵 댓글 감사합니다~^^

    gu3735
    2021.07.02 19:36

    혹시 제가 본사 출장자수를 잘못이해하고있나요? 
    식사가능에서 뺄 이유가 있지않나요?? ㅎ

    Henry_Lee
    2021.07.02 19:49

    비슷한 질문 주셨네요..
    ---복붙---
    휴가자, 재택근무자와는 달리 사무실에 체류할 가능성이 있다고 판단한 접근이었습니다.
    예를 들어, '출장을 13시에 나간다면, 밥을 먹고 가지 않을까?' 하는 것이죠.

    gu3735
    2021.07.02 23:25

    아이고;;; 위에글 보고 달걸...ㅋㅋㅋ
    감사합니다 ㅎㅎ 궁금했습니다 ㅎㅎ 합리적 추론이네요! ㅎ

    DM_MSI
    2021.07.12 01:13

    쉽게 잘 설명해주셔서 감사합니다~!

    Henry_Lee
    2021.07.16 11:41

    댓글 감사합니다 =D

    soddy
    2021.07.14 15:07

    혹시 mse는 어디서 확인하나요? 

    Henry_Lee
    2021.07.16 11:41

    코드에서
    'mae' -> 'mse' 하거나,
    'neg_mean_absolute_error' -> 'neg_mean_squared_error' 로
    한번 해보시겠어요~?

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