September 2023
Beginner to intermediate
1044 pages
27h 52m
Korean
Content preview from 핸즈온 머신러닝(3판)
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340
1
부
머신러닝
가우스 혼합 모델이 잘 작동합니다.
TIP
k
-평균을 실행하기 전에 입력 특성의 스케일을 맞추는 것이 중요합니다(
2
장 참고). 그렇지 않으면 클러스터가
길쭉해지고
k
-평균의 결과가 좋지 않습니다. 특성의 스케일을 맞추어도 모든 클러스터가 잘 구분되고 원형을
형태를 가진다고 보장할 수는 없지만 일반적으로
k
-평균에 도움이 됩니다.
이제 군집에서 도움을 받을 수 있는 몇 가지 방법을 살펴보겠습니다.
k
-평균을 사용하지만 다
른 군집 알고리즘으로도 자유롭게 실험해보세요.
9.1.3
군집을 사용한 이미지 분할
이미지 분할
image
segmentation
은 이미지를 여러 개의
세그먼트
segment
로 분할하는 작업입니다. 여기
에는 여러 가지 변형이 있습니다.
•
색상 분할
동일한 색상을 가진 픽셀을 같은 세그먼트에 할당합니다. 많은 애플리케이션에서는 이 정도로 충분합니다.
예를 들어 인공위성 사진을 분석하여 한 지역의 전체 산림 면적이 얼마나 되는지 측정하려면 색상 분할로
충분합니다.
•
시맨틱 분할
동일한 종류의 물체에 속한 모든 픽셀을 같은 세그먼트에 할당합니다. 예를 들어 자율 주행 자동차의 비전
시스템에서 보행자 이미지를 구성하는 모든 픽셀은 ‘보행자’ 세그먼트에 할당될 것입니다.
•
인스턴스 분할
개별 객체에 속한 모든 픽셀을 같은 세그먼트에 ...
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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.