목록SVR (1)
David의 개발 이야기!
![](http://i1.daumcdn.net/thumb/C150x150/?fname=https://blog.kakaocdn.net/dn/bDwiL9/btrL7vgb7qU/wwvlJehRL51LUHKrhNDgQ1/img.png)
sklearn, 서포트벡터 머신을 활용해서, 호봉에 따른 임금상승을 구해보자! 1. Import Libraries 2. Import Dataset 3. Feature Scaling 4. Training the SVR model 5. Predicting the new result 6. Visualizing the SVR results. 다음과 같은 순서로 분석하고자 한다! 1. Import libraries import numpy as np import pandas as pd import matplotlib.pyplot as plt 2. Import Dataset dataset = pd.read_csv("Position_Salaries.csv") x = dataset.iloc[:,1:-1].values y..
Udemy Python Machine Learning A-Z
2022. 9. 14. 18:04