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유저의 과거 문제 풀이 데이터를 바탕으로 마지막 문제의 정답 여부 예측 Competition (Naver Boostcamp)

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Team. 멘토스

Wrap-Up Report

LGBM

  • LGBMwithAggData : Training LGBM with aggregation data
  • LGBMwithRowData : Training LGBM with row(sequential) data

install

pip install -r requirements.txt

How to use

  • README.md in directory

LB score

  • LGBMwithAggData Best LB auc : 0.7313
  • LGBMwithRowData Best LB auc : 0.7893

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유저의 과거 문제 풀이 데이터를 바탕으로 마지막 문제의 정답 여부 예측 Competition (Naver Boostcamp)

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  • Jupyter Notebook 85.0%
  • Python 15.0%