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我正在做一個多元線性迴歸，並試圖選擇一些自變量的最佳子集。我想嘗試在「for」循環中執行所有1024個可能的組合，並根據條件編號和r平方保存最佳結果。我知道這兩種計算，給出類似的結果：如何從statsmodels.api.OLS獲取條件編號？
model = sm.OLS(salarray, narraycareer)
results = model.fit()
print results.summary()
OLS Regression Results
==============================================================================
Dep. Variable: y R-squared: 0.425
Model: OLS Adj. R-squared: 0.409
Method: Least Squares F-statistic: 26.89
Date: Sat, 23 Sep 2017 Prob (F-statistic): 1.69e-27
Time: 00:58:14 Log-Likelihood: -1907.4
No. Observations: 263 AIC: 3831.
Df Residuals: 255 BIC: 3859.
Df Model: 7
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [95.0% Conf. Int.]
------------------------------------------------------------------------------
const 535.9259 21.387 25.058 0.000 493.808 578.044
x1 -675.5296 302.245 -2.235 0.026 -1270.744 -80.315
x2 182.7168 436.493 0.419 0.676 -676.874 1042.307
x3 -48.2603 126.141 -0.383 0.702 -296.671 200.151
x4 445.0863 218.373 2.038 0.043 15.043 875.130
x5 344.0092 219.896 1.564 0.119 -89.035 777.053
x6 -41.5168 71.925 -0.577 0.564 -183.159 100.126
x7 96.5430 30.595 3.156 0.002 36.293 156.793
==============================================================================
Omnibus: 96.442 Durbin-Watson: 1.973
Prob(Omnibus): 0.000 Jarque-Bera (JB): 440.598
Skew: 1.438 Prob(JB): 2.11e-96
Kurtosis: 8.651 Cond. No. 61.7
==============================================================================
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
>>>
但我不能找到如何走出條件數或R平方的任何文件。
謝謝！