May 2020
Beginner to intermediate
952 pages
24h 11m
Korean
Content preview from 핸즈온 머신러닝(2판): 사이킷런, 케라스, 텐서플로 2를 활용한 머신러닝, 딥러닝 완벽 실무
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234
1
부
머신러닝
6.3
클래스 확률 추정
결정 트리는 한 샘플이 특정 클래스
k
에 속할 확률을 추정할 수도 있습니다. 먼저 이 샘플
에 대해 리프 노드를 찾기 위해 트리를 탐색하고 그 노드에 있는 클래스
k
의 훈련 샘플의 비
율을 반환합니다. 예를 들어 길이가
5cm
이고 너비가
1
.
5cm
인 꽃잎을 발견했다고 가정합시
다. 이에 해당하는 리프 노드는 깊이
2
에서 왼쪽 노드이므로 결정 트리는 그에 해당하는 확
률을 출력합니다. 즉,
Iris
-
Setosa
는
0
%(
0
/
54
),
Iris
-
Versicolor
는
90
.
7
%(
49
/
54
),
Iris
-
Virginica
는
9
.
3
%(
5
/
54
)입니다. 만약 클래스를 하나 예측한다면 가장 높은 확률을 가진
Iris
-
Versicolor
(클래스
1
)를 출력할 것입니다. 확인해봅시다.
>>> tree_clf.predict_proba([[5, 1.5]])
array([[0. , 0.90740741, 0.09259259]])
>>> tree_clf.predict([[5, 1.5]])
array([1])
정확하네요! 추정된 확률은 [그림
6
-
2
]의 오른쪽 아래 사각형 안에서는 어느 위치든 동일합니
다.
2
예를 들어 길이가
6cm
이고 너비가
1
.
5cm
인 꽃잎도 확률이 같습니다(사실 이 경우에는
Iris
-
Virginica
에 더 가까워 보입니다 ).
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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.