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파이썬 라이브러리를 활용한 머신러닝(번역개정판): 사이킷런 핵심 개발자가 쓴 머신러닝과 데이터 과학 실무서
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파이썬 라이브러리를 활용한 머신러닝(번역개정판): 사이킷런 핵심 개발자가 쓴 머신러닝과 데이터 과학 실무서

by 박해선, 안드레아스 뮐러, 세라 가이도
April 2019
Beginner to intermediate
480 pages
12h 34m
Korean
Hanbit Media, Inc.
Content preview from 파이썬 라이브러리를 활용한 머신러닝(번역개정판): 사이킷런 핵심 개발자가 쓴 머신러닝과 데이터 과학 실무서
284
파이썬 라이브러리를 활용한 머신러닝(번역개정판)
In [17]:
logreg = LogisticRegression()
logreg.t(X_train_trans, y_train)
X_test_trans = ct.transform(X_test)
print("테스트 점수: {:.2f}".format(logreg.score(X_test_trans, y_test)))
Out [17]:
테스트 점수: 0.81
이 경우에 데이터의 스케일이 영향을 미치지 못했습니다. 하나의 변환기로 모든 전처리 단계를
캡슐화하면 장점이 더 있습니다. 나중에 이에 대해 설명하겠습니다.
ColumnTransformer
의 단계에 접근하려면
named
_
transformers
_ 속성을 사용합니다.
In [18]:
ct.named_transformers_.onehot
Out [18]:
OneHotEncoder(categorical_features=None, categories=None,
dtype=<class 'numpy.oat64'>, handle_unknown='error',
n_values=None, sparse=False)
4.3
make
_
column
_
transformer
로 간편하게
ColumnTransformer
만들기
앞서 설명한 대로
ColumnTransformer
를 만들면 ...
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Publisher Resources

ISBN: 9791162241646