May 2018
Beginner to intermediate
672 pages
16h 54m
Korean
Content preview from 핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무
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266
1
부
머신러닝
그림
7-15
멀티 레이어 스태킹 앙상블의 예측
레이어 3
레이어 2
레이어 1
새로운 샘플
안타깝게도 사이킷런은 스태킹을 직접 지원하지 않습니다. 하지만 직접 구현하는 것이 그리 어
렵지는 않습니다(다음 연습문제를 참조하세요 ). 아니면
brew
34
같은 오픈소스 구현을 사용할
수 있습니다 (
http
://
github
.
com
/
viisar
/
brew
).
7.7
연습문제
1
.
정확히 같은 훈련 데이터로 다섯 개의 다른 모델을 훈련시켜서 모두
95
% 정확도를 얻었다
면 이 모델들을 연결하여 더 좋은 결과를 얻을 수 있을까요? 가능하다면 어떻게 해야 할까
요? 그렇지 않다면 왜일까요?
34
옮긴이_
macOS
용 패키지 관리자인
Homebrew
의
brew
명령과 혼동하지 마세요.
267
7
장
앙상블 학습과 랜덤 포레스트
2
.
직접 투표와 간접 투표 분류기 사이의 차이점은 무엇일까요?
3
.
배깅 앙상블의 훈련을 여러 대의 서버에 분산시켜 속도를 높일 수 있을까요? 페이스팅 앙
상블, 부스팅 앙상블, 랜덤 포레스트, 스태킹 앙상블의 경우는 어떨까요?
4
.
oob
평가의 장점은 무엇인가요?
5
.
무엇이 엑스트라 트리를 일반 랜덤 포레스트보다 더 무작위하게 만드나요? 추가적인 무작
위성이 어떻게 도움이 될까요? 엑스트라 트리는 일반 랜덤 포레스트보다 ...
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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.