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    SW중심대학 공동 AI 경진대회 ❮예선❯

    SW중심대학 | 예선 | 심리성향 | AUC

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    [아주대] Private 19위: bagging_et + boosting_et + blend_et&rf

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    2022.08.28 01:24 1,815 Views language
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    데이터 전처리는 따로 안해줬습니다.
    pycaret을 이용해 구현했고, 수치형 컬럼 값이 NaN일 경우에는 평균값으로, 범주형 컬럼 값이 NaN일 경우에는 최빈값으로 넣어줬습니다.
    compare_model 결과 extra tree, random forest의 성능이 우월하게 좋았습니다.
    이를 이용해 여러 모델을 만들었고, 실제 제출 결과 bagging_et, boosting_et, blend_et&rf가 성능이 가장 좋았습니다.
    최종적으로 위 3개 모델의 예측 결과를 soft voting하였습니다.

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    [아주대] Private 19위: bagging_et + boosting_et + blend_et&rf
    Competition - SW중심대학 공동 AI 경진대회 ❮예선❯
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