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농산물 데이터 분석을 통한 가격 예측 AI model별 비교

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iDolphin99/proj-argricultural-price-predict

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XGBOOST

  • isZero csv (무 442 / 배추 444 / 건고추 986 / 마늘 466 / 대파 442)
  • NoZero csv -> 평균값으로 채우거나, 삭제하거나
  • 28 feature (default 12 + new 16) csv
  • 무/배추/건고추/마늘/대파
  • feature importance
  • evaluation -> logloss, rmse, acurracy, etc...

LightGBM

RNN

LSTM

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농산물 데이터 분석을 통한 가격 예측 AI model별 비교

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