December 2024
Beginner to intermediate
336 pages
7h 41m
Korean
Content preview from 로우코드 AI
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116
로우코드 AI
평균 절대 오차(
MAE
)
MAE
는 예측값과 실젯값 사이의 평균 절대 오차를 측정한 값입니다. 이는 예측값과 실젯값 사이의 차이의 절댓
값들에 대한 평균을 구한 것으로,
MAE
값이 낮을수록 모델의 예측이 실젯값에 더 가까움을 의미합니다. 이 예
시에서는
MAE
값이
0
.
304
정도일 때 모델의 정확도가 상당히 높다고 할 수 있습니다.
평균 절대 백분율 오차(
MAPE
)
MAPE
는 절대 백분율 오차의 평균으로, 값이 낮을수록 모델의 품질이 높음을 의미합니다.
MAPE
값의 범위는
0
~
100
%이며, 이 값이 낮을수록 모델의 예측이 우수하다는 뜻입니다. 이 예시에서는
MAPE
값이
2
.
28
정도
일 때 모델의 예측 정확도가 상당히 높다고 할 수 있습니다.
4.3.6
모델의 특징 중요도
모델의 특징 중요도는 각 특징이 모델 학습에 얼마나 영향을 미쳤는지를 파악하게 해줍니다.
[그림
4
-
32
]는 백분율로 표시된 중요도를 보여줍니다. 백분율이 높을수록 상관관계, 즉 해당
특징이 모델에 더 큰 영향을 미쳤음을 의미합니다. 특징 중요도를 통해 [그림
4
-
32
]처럼 학습
된 모델에 가장 크게 기여한 특징을 쉽게 확인할 수 있습니다.
그림
4-32
광고 데이터셋의 특징 중요도
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.