資料載入

x,y = [],[]
with open('abnormal.txt','r') as f:
    for line in f.readlines():
        data =  [float(substr) for substr in line.split(',')]   #遍歷每行的資料新增到ｄａｔａ
        x.append(data[:-1])    #特徵矩陣
        y.append(data[-1])      #標籤
x = np.array(x)
y = np.array(y)

建立模型

model = lm.LinearRegression
 
()
model.fit(x,y)
# 預測
pred_y = model.predict(x)

視覺化

mp.figure("Linear Regression",facecolor='lightgray')
mp.title("Linear Regression",fontsize = 10)
mp.xlabel("x",fontsize = 10)
mp.ylabel('y',fontsize = 10)
mp.tick_params(labelsize =10)
mp.grid(linestyle = ':')
mp.scatter(x,y,c = 'dodgerblue',alpha=0.75
 
,s = 60,label = 'Sample')
sorted_indics = x.T[0].argsort()
mp.plot(x[sorted_indics],pred_y,c = 'orangered',label = 'Regression')
mp.legend()
mp.show()

模型的儲存和過載

#匯入序列化和反序列化的模組
import pickle 
#模型儲存
with open('linear.pkl','wb') as f:
    pickle.dump(model,f) 
with open('linear.pkl','rb') as f:
    model_new = pickle.load
 
(f)