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dacon_temperature_predict

DACON AI프렌즈 시즌1 온도 추정 경진대회

학습

  • train, dev set
    • Y0~17만 가지는 경우를 train set으로 하고 해당 평균값을 label로 사용.
    • Y18이 주어진 경우는 dev set으로 사용.
    • train set으로 학습 후 dev set에서의 점수가 가장 높은 epoch 모델을 선택.
  • features
    • 기온, 현지기압, 풍속 등 8 종류의 features를 학습.
      • feature마다 5개의 연속적인 값을 가짐.
    • feature 당 각각의 Bi-LSTM으로 학습.
    • 8개 LSTM의 output을 concat 후 Linear 연산으로 1개의 값으로.
  • MSELoss 사용.

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