scikit-learn 개요
scikit-learn 패키지는 지도학습, 비지도학습 등 대부분의 머신러닝 알고리즘을 제공하고 있으며, Python에서 머신러닝을 수행할 때 굉장히 많이 쓰이는 패키지 중의 하나다
Install Package
1 | pip install -U scikit-learn # -U: Update |
Note: you may need to restart the kernel to use updated packages.
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
1 | from sklearn.linear_model import LinearRegression |
3 Steps to Fit Model and Do Prediction
STEP 1. 모델 정의
1 | from sklearn.linear_model import LinearRegression |
STEP 2. 학습 (Fit in Training set)
- 명령어: model_name .fit
1 | model.fit(x_train, y_train) |
STEP 3. 예측 (Predict in Test set)
- 명령어: model_name .predict
1 | prediction = model.predict(x_test) |