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    Thyroid Cancer Diagnosis Classification Hackathon : Accurately distinguish between benign and malignant using AI!

    Dacon Hackathon | Algorithm | Begin | Tabular | Classification | F1 Score

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    Private 6위 | XGB + LGBM + CatBoost | 클래스 가중치 Threshold 최적화

    한국식_러다이트_운동원
    2025.07.02 21:27 433 Views language
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    XGBoost + LightGBM + CatBoost 스태킹 앙상블, 클래스 불균형 가중치 적용, 범주형 전용 원-핫 인코딩, 메타 모델 Logistic Regression, Threshold 최적화, Fold별 F1 출력, 자동 버전 관리 적용 모델

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    Private 2위, LGBM 모델, OrdinalEncoder 전처리 활용
    Competition - 갑상선암 진단 분류 해커톤 : 양성과 악성, AI로 정확히 구분하라!
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    Private 6위 | XGB + LGBM + CatBoost | 클래스 가중치 Threshold 최적화
    Competition - 갑상선암 진단 분류 해커톤 : 양성과 악성, AI로 정확히 구분하라!
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    Private 7위 / 딥러닝 기반 다층 퍼셉트론 모델 / 기본적인 인코딩 및 정규화 기법 사용
    Competition - 갑상선암 진단 분류 해커톤 : 양성과 악성, AI로 정확히 구분하라!
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