May 2021
Beginner to intermediate
380 pages
9h 22m
Korean
Content preview from 데이터 과학을 위한 통계(2판)
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245
5
장
분류
그림
5-3
오즈비와 로그 오즈비 사이의 관계
수치형 변수
X
에 대해서도 마찬가지로 비슷한 의미를 갖는다.
X
에서 단위 크기만큼 변화할 때
오즈비에서의 변화를 생각할 수 있다. 예를 들면 소득에 대비 상환의 비율이
5
에서
6
만큼 증가
했다고 하면,
exp
(
0
.
08244
) ≈
1
.
09
만큼 연체할 오즈비가 증가한다. 변수
borrower
_
score
는 대출자의 신용도를 나타내며
0
(낮음)에서
1
(높음)까지 변화한다. 현재 연체 중인 최악의
차용인에 대한 가장 우수한 차용인의 오즈비는
exp
(-
4
.
61264
) ≈
0
.
01
정도로 훨씬 더 적
다. 즉, 가장 신용이 불량한 차용인의 연체 위험도는 신용이 가장 좋은 차용자에 비해
100
배 정
도이다!
5.3.6
선형회귀와 로지스틱 회귀: 유사점과 차이점
선형회귀와 로지스틱 회귀는 공통점이 많다. 두 가지 모두 예측변수와 응답변수를 선형 관계로
가정한다. 가장 좋은 모델을 탐색하고 찾는 과정도 아주 유사하다. 대부분의 선형모형에서, 예
측변수에 스플라인 변환 (
4
.
7
.
2
절 참고)을 사용하는 방법은 로지스틱 회귀 설정에서도 똑같이
적용할 수 있다. 하지만 로지스틱 회귀는 아래 두 가지 점에서 근본적인 차이가 있다.
246
데이터 과학을 위한 통계
•
모델을 피팅하는 방식 (최소제곱을 사용할 수 없다 )
•
모델에서 ...
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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.