trained 예문

• I trained him.
  조련을 했죠 배우는 게 더뎠지만 배우긴 하더군요 I trained him.
• I was also trained to kill my enemies, your Grace.
  I was also trained to kill my enemies, your Grace. 그리고 제 적을 죽이도록 훈련받았지요, 폐하.
• Your older brother was trained to lead and you were trained to follow.
  Your older brother was trained to lead and you were trained to follow. 당신 형이 이끌고 당신이 따르도록 훈련받았겠죠.
• Your older brother was trained to lead and you were trained to follow.
  Your older brother was trained to lead and you were trained to follow. 당신 형이 이끌고 당신이 따르도록 훈련받았겠죠.
• If the wind is with them, wolves can track a scent by a distance of two miles, which means we can draw them to us... [growls] Or into a trap.
  훈련된 사냥꾼들도 후각으로 쫒을 수 있지 A trained hunter can use scent to track them.
• Reserve the observation as validation data, and train the model using the other n – 1 observations. Store the n compact, trained models in the cells of an n -by-1 cell vector in the Trained property of the cross-validated model.
  관측값을 검증 데이터로 예약하고 이외의 n – 1개 관측값을 사용하여 모델을 훈련시킵니다. 교차 검증된 모델의 Trained 속성에 n x1 셀형 벡터의 셀로 n 개의 훈련된 간소 모델을 저장합니다.
• Reserve the observation as validation data, and train the model using the other n – 1 observations. Store the n compact, trained models in the cells of an n -by-1 cell vector in the Trained property of the cross-validated model.
  관측값을 검증 데이터로 예약하고 이외의 n – 1개 관측값을 사용하여 모델을 훈련시킵니다. 교차 검증된 모델의 Trained 속성에 n x1 셀형 벡터의 셀로 n 개의 훈련된 간소 모델을 저장합니다.
• For each set, reserve the set as validation data, and train the model using the other k – 1 sets. Store the k compact, trained models in the cells of a k -by-1 cell vector in the Trained property of the cross-validated model.
  각 세트마다 해당 세트를 검증 데이터로 예약하고 나머지 k – 1 개의 세트를 사용하여 모델을 훈련시킵니다. 교차 검증된 모델의 Trained 속성에 k x1 셀형 벡터의 셀로 k 개의 훈련된 간소 모델을 저장합니다.
• For each set, reserve the set as validation data, and train the model using the other k – 1 sets. Store the k compact, trained models in the cells of a k -by-1 cell vector in the Trained property of the cross-validated model.
  각 세트마다 해당 세트를 검증 데이터로 예약하고 나머지 k – 1 개의 세트를 사용하여 모델을 훈련시킵니다. 교차 검증된 모델의 Trained 속성에 k x1 셀형 벡터의 셀로 k 개의 훈련된 간소 모델을 저장합니다.