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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227
6
장
결정 트리
그림
6-1
붓꽃 결정 트리
꽃잎 길이
꽃잎 너비
6.2
예측하기
[그림
6
-
1
]의 트리가 어떻게 예측을 만들어내는지 살펴보겠습니다. 새로 발견한 붓꽃의 품종을
분류하려 한다고 가정하겠습니다. 먼저 루트 노드
root
node
(깊이가
0
인 맨 꼭대기의 노드 )에서
시작합니다. 이 노드는 꽃잎의 길이가
2
.
45cm
보다 짧은지 검사합니다. 만약 그렇다면 루트 노
드에서 왼쪽의 자식 노드
child
node
(깊이
1
, 왼쪽 노드)로 이동합니다. 이 경우 이 노드가 리프 노
드
leaf
node
(즉, 자식 노드를 가지지 않는 노드 )이므로 추가적인 검사를 하지 않습니다. 그냥 노드
에 있는 예측 클래스를 보고 결정 트리가 새로 발견한 꽃의 품종을
Iris
-
Setosa
(
class
=
setosa
)
라고 예측합니다.
또 다른 꽃을 발견했는데 이번에는 꽃잎의 길이가
2
.
45cm
보다 깁니다. 이번에는 루트 노드의
오른쪽 자식 노드로 이동해야 합니다. 이 노드는 리프 노드가 아니라서 추가로 ‘꽃잎의 너비가
1
.
75cm
보다 작은지’ 검사합니다. 만약 그렇다면 이 꽃은 아마도
Iris
-
Versicolor
(깊이
2
, 왼
228
1
부
머신러닝
쪽)일 것입니다. 그렇지 않다면
Iris
-
Virginica
(깊이
2
, 오른쪽)일 것입니다. 아주 간단명료하
네요.
NOTE
_
결정 트리의 여러 ...
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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.