May 2021
Beginner to intermediate
380 pages
9h 22m
Korean
Content preview from 데이터 과학을 위한 통계(2판)
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358
데이터 과학을 위한 통계
NOTE
_
모델 기반 클러스터링은 실제로 매우 활발하고 빠르게 발전하는 연구 분야이다. 본문에서 다루는
적용 범위는 아주 일부에 지나지 않는다. 실제로
mclust
도움말 파일만 해도
154
쪽 분량이다. 모델 기반 클
러스터링의 미묘한 내용까지 다루는 것은 데이터 과학자들이 그간 접한 대부분의 문제보다 더 많은 노력이
필요할 수 있다.
모델 기반 클러스터링 기술에는 몇 가지 한계가 있다. 이 방법은 기본적으로 데이터들이 모델
을 따른다는 가정이 필요하며, 클러스터링 결과는 이 가정에 따라 매우 다르다. 필요한 계산량
역시 계층적 클러스터링보다 높으므로 대용량 데이터로 확장하기가 어렵다. 마지막으로 알고
리즘이 다른 방법들보다 더 복잡하고 이용하기가 어렵다.
주요 개념
• 클러스터들이 각자 서로 다른 확률분포로부터 발생한 것으로 가정한다.
• 분포 (일반적으로 정규분포 ) 개수에 대한 가정에 따라 서로 다른 적합한 모델이 있다.
• 이 방법은 너무 많은 파라미터 (오버피팅의 원인이 될 수 있다 )를 사용하지 않으면서도 데이터에 적합한 모
델(그리고 연관된 클러스터 개수 )을 선택한다.
7.4.4
더 읽을 거리
•모델 기반 클러스터링에 대한 내용은
mclust
와
GaussianMixture
의 문서를 참고하자.
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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.