res = pd.DataFrame(res, columns=['prob_positive', 'prob_negative'])
return res
prob_gpt_4o = make_exp('gpt-4o', df)
prob_gpt_4o_mini = make_exp('gpt-4o-mini', df)
변수
prob
_
gpt
_
4o
와
prob
_
gpt
_
4o
_
mini
는 각각
200
개의 행과
2
개의 열을 가진 데이터 프
레임입니다. 각 열은 텍스트가 긍정적일 확률과 부정적일 확률을 나타냅니다. 실제 정답이 있
는
df
데이터셋이 있기 때문에 모델의 성능을 추정할 수 있습니다.
모델의 정확도를 추정하는 한 가지 방법은 두 모델이 제공하는 확률을 이진 예측(
0
또는
1
)으
로 변환하는 것입니다. 확률을 분류할 기준인 임곗값은 간단하게
0
.
5
로 설정합니다. 임곗값 이 ...
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