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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188
1
부
머신러닝
y
_
val
_
predict
=
sgd
_
reg
.
predict
(
X
_
val
_
poly
_
scaled
)
val
_
error
=
mean
_
squared
_
error
(
y
_
val
,
y
_
val
_
predict
)
if val
_
error
<
minimum
_
val
_
error
:
minimum
_
val
_
error
=
val
_
error
best
_
epoch
=
epoch
best
_
model
=
clone
(
sgd
_
reg
)
warm
_
start
=
True
로 지정하면
fit
( )
메서드가 호출될 때 처음부터 다시 시작하지 않고 이전
모델 파라미터에서 훈련을 이어갑니다.
4.6
로지스틱 회귀
1
장에서도 이야기한 것처럼, 어떤 회귀 알고리즘은 분류에서도 사용할 수 있습니다 (또는 그
반대의 경우도 있습니다 ). 로지스틱 회귀
Logistic
Regression
(또는 로짓 회귀
Logit
Regression
)는 샘플이
특정 클래스에 속할 확률을 추정하는 데 널리 사용됩니다 (예를 들면 이 이메일이 스팸일 확률
은 얼마인가?). 추정 확률이
50
%가 넘으면 모델은 그 샘플이 해당 클래스에 속한다고 예측합
니다 (즉, 레이블이 ‘
1
’인 양성 클래스 ). 아니면 클래스에 속하지 않는다고 예측합니다 (즉, 레
이블이 ‘
0
’인 음성 클래스 ). 이를 이진 분류기라고 합니다.
4.6.1
확률 추정
그렇다면 ...
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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.