Day2 簡單限行迴歸實現

1.匯入資料集

2. 如果需要對資料集進行空值處理，特徵化處理

3. 拆分資料集為訓練集和測試集

4. 使用訓練集使用簡單線性迴歸模型來訓練

5. 預測結果

6. 訓練集結果視覺化。測試集結果視覺化

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data = pd.read_csv(r'd:\Users\lulib\Desktop\data.txt',sep='\t')
X = data.iloc[:,:-1].values
Y = data.iloc[:,-1].values
X_train, X_test, Y_train, Y_test = train_test_split( X,Y,test_size = 0.25, random_state = 0)
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor = regressor.fit(X_train,Y_train)
Y_pred = regressor.predict(X_test)
plt.plot(X_train,Y_train,'r.',X_train,regressor.predict(X_train),'b-')