Python线性回归

我需要在多元线性回归中检查这些标准，以便进行循环：

• p值<0.05
• F-统计<0.05
• R^2>=0.8

我使用以下代码：

X = df.iloc[:,2:].values

Y = df.iloc[:,1].values

from sklearn.model_selection import train_test_split

X_train, X_test, Y_train, Y_test =  train_test_split(X,Y,test_size = 0.2, random_state= 0)

from sklearn.preprocessing import StandardScaler

sc_X = StandardScaler()

X_train = sc_X.fit_transform(X_train)

X_test = sc_X.transform(X_test)

from sklearn.linear_model import LinearRegression

regressor = LinearRegression()

regressor.fit(X_train, Y_train)

Y_pred = regressor.predict(X_test)

df1 = pd.DataFrame({'Actual': Y_test.flatten(), 'Predicted': Y_pred.flatten()})

df1.plot(kind='bar')

plt.grid(which='major', linestyle='-', linewidth='0.5', color='green')

plt.grid(which='minor', linestyle=':', linewidth='0.5', color='black')

plt.show()

import statsmodels.formula.api as sm

X= np.append (arr = np.ones((141,1)).astype(int), values = X, axis = 1)

X_opt = X[:,[0,1,2,3,4,5]]

regressor_OLS = sm.OLS(endog = Y, exog = X_opt).fit()

regressor_OLS.summary()

输出为：

我如何定义标准，使其具有可比性？它们需要在每个循环中接收不同的值

谢谢：）