October 2021
Beginner to intermediate
416 pages
9h 3m
Korean
Content preview from 살아 움직이는 머신러닝 파이프라인 설계: 텐서플로와 함께하는 머신러닝 프로젝트 자동화
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162
살아 움직이는 머신러닝 파이프라인 설계
7.1.2
회귀 지표
회귀 분석 문제에서 모델은 각 학습 예제에서 일부 수치를 예측하며, 이 값을 실젯값과 비교합
니다.
TFMA
에서 사용할 수 있는 일반적인 회귀 지표는 다음과 같습니다.
●
평균 절대 오차
Mean
Absolute
Error
(MAE )
MAE
는 다음과 같이 정의합니다.
여기서
n
은 학습 예제의 수이고,
y
는 참값이며,
ŷ
은 예측값입니다. 각 학습 예제에서 예측값과 실젯값 사이의
절대 차이가 계산됩니다. 즉,
MAE
는 모델이 생성하는 평균 오차입니다.
●
평균 절대 백분율 오차
Mean
absolute
percentage
error
(MAPE )
MAPE
는 다음과 같이 정의합니다.
이름에서 알 수 있듯이, 이 지표는 모든 예제에 대한 백분율 오차를 제공합니다. 이것은 모델이 체계적인 오차
를 범할 때 특히 유용합니다.
●
평균 제곱 오차
Mean
squared
error
(MSE )
MSE
는 다음과 같이 정의합니다.
y
–
ŷ
항이 제곱이라는 점을 제외하면
MAE
와 같습니다. 따라서 전체 오류에 대한 특이치의 효과가 훨씬 더
커집니다.
비즈니스 문제에 적합한 지표를 선택한 다음 단계는 시스템 학습 파이프라인에 해당 지표를 포
함시키는 것입니다. 다음 절에서 설명하는
TFMA
를 사용하여 ...
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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.