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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150
1
부
머신러닝
>>>
y
_
train
_
knn
_
pred
=
cross
_
val
_
predict
(
knn
_
clf
,
X
_
train
,
y
_
multilabel
,
cv
=
3,
n
_
jobs
=-
1)
>>>
f1
_
score
(
y
_
multilabel
,
y
_
train
_
knn
_
pred
,
average
=
"
macro
")
0
.
97709078477525
실제로는 아닐 수 있지만 이 코드는 모든 레이블의 가중치가 같다고 가정한 것입니다. 특히 앨
리스 사진이 밥이나 찰리 사진보다 훨씬 많다면 앨리스 사진에 대한 분류기의 점수에 더 높은 가
중치를 둘 것입니다. 간단한 방법은 레이블에 클래스의 지지도
support
(즉, 타깃 레이블에 속한
샘플 수 )를 가중치로 주는 것입니다. 이렇게 하려면 이전 코드에서
average
=
"
weighted
"
로 설
정하면 됩니다.
15
3.7
다중 출력 분류
마지막으로 알아볼 분류 작업은 다중 출력 다중 클래스 분류
multioutput
-
multiclass
classification
(또는 간
단히 다중 출력 분류
multioutput
classification
)입니다. 다중 레이블 분류에서 한 레이블이 다중 클래
스가 될 수 있도록 일반화한 것입니다 (즉, 값을 두 개 이상 가질 수 있습니다).
이를 위해 이미지에서 노이즈를 제거하는 시스템을 만들어보겠습니다. 노이즈가 많은 ...
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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.