scikit-learn 개요


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scikit-learn 패키지는 지도학습, 비지도학습 등 대부분의 머신러닝 알고리즘을 제공하고 있으며, Python에서 머신러닝을 수행할 때 굉장히 많이 쓰이는 패키지 중의 하나다

sk_learn


Install Package

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pip install -U scikit-learn  # -U: Update
Note: you may need to restart the kernel to use updated packages.

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Usage:   
  D:\Anaconda\python.exe -m pip install [options] <requirement specifier> [package-index-options] ...
  D:\Anaconda\python.exe -m pip install [options] -r <requirements file> [package-index-options] ...
  D:\Anaconda\python.exe -m pip install [options] [-e] <vcs project url> ...
  D:\Anaconda\python.exe -m pip install [options] [-e] <local project path> ...
  D:\Anaconda\python.exe -m pip install [options] <archive url/path> ...

no such option: -:

Import Functions from Sub-packages

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from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split

3 Steps to Fit Model and Do Prediction

STEP 1. 모델 정의

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from sklearn.linear_model import LinearRegression
model = LinearRegression()

STEP 2. 학습 (Fit in Training set)

  • 명령어: model_name .fit
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model.fit(x_train, y_train)

STEP 3. 예측 (Predict in Test set)

  • 명령어: model_name .predict
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prediction = model.predict(x_test)