May 2020
Beginner to intermediate
952 pages
24h 11m
Korean
Content preview from 핸즈온 머신러닝(2판): 사이킷런, 케라스, 텐서플로 2를 활용한 머신러닝, 딥러닝 완벽 실무
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58
1
부
머신러닝
1.5.4
관련 없는 특성
속담에도 있듯이 엉터리가 들어가면 엉터리가 나옵니다
garbage
in
,
garbage
out
. 훈련 데이터에 관련
없는 특성이 적고 관련 있는 특성이 충분해야 시스템이 학습할 수 있을 것입니다. 성공적인 머신
러닝 프로젝트의 핵심 요소는 훈련에 사용할 좋은 특성들을 찾는 것입니다. 이 과정을
특성 공학
feature
engineering
이라 하며 다음과 같은 작업입니다.
●
특성 선택
feature
selection
: 가지고 있는 특성 중에서 훈련에 가장 유용한 특성을 선택합니다.
●
특성 추출
feature
extraction
: 특성을 결합하여 더 유용한 특성을 만듭니다. 앞서 본 것처럼 차원 축소 알고리
즘이 도움이 될 수 있습니다.
●
새로운 데이터를 수집해 새 특성을 만듭니다.
지금까지 나쁜 데이터의 사례를 살펴보았고 이제 나쁜 알고리즘의 예를 몇 가지 살펴보겠습니다.
1.5.5
훈련 데이터 과대적합
해외여행 중 택시운전사가 내 물건을 훔쳤다고 가정합시다. 아마도 그 나라의
모든
택시운전사
를 도둑이라고 생각할 수도 있습니다. 사람은 종종 과도하게 일반화를 하지만 주의하지 않으면
기계도 똑같은 함정에 빠질 수 있습니다. 머신러닝에서는 이를
과대적합
overfitting
이라고 합니다.
이는 모델이 훈련 데이터에
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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.