GLM结果返回偏差= nan

Question

Python GLM摘要结果返回nan的Deviance值

我是Python和数据科学的新手。我正在Jupyter中运行广义线性模型。 GLM的结果显示nan的偏差值。这也影响了AIC。

该模型混合了类别变量（〜25）和连续变量（6）。

#Assign the dataframe to the X variable and drop the response variable "fully_funded"
X = p2o_mstr_df6.drop("fully_funded",axis=1)

X = sm.add_constant(X)

Y = p2o_mstr_df6["fully_funded"]

# all Y variables are 1 or 0 and dtype = int64

#Fit the logistic regression for the dataset
logit = sm.GLM(Y, X, family=sm.families.Binomial())

result = logit.fit()

print(result.summary())

np.exp(result.params)

我不确定如何解决Deviance = nan的问题。我正在尝试改善模型的结果，但需要能够在后续迭代中比较Deviance和AIC。

Generalized Linear Model Regression Results                  
==============================================================================
Dep. Variable:           fully_funded   No. Observations:               131329
Model:                            GLM   Df Residuals:                   131298
Model Family:                Binomial   Df Model:                           30
Link Function:                  logit   Scale:                          1.0000
Method:                          IRLS   Log-Likelihood:                    nan
Date:                Fri, 28 Jun 2019   Deviance:                          nan
Time:                        12:45:53   Pearson chi2:                 9.01e+15
No. Iterations:                   100   Covariance Type:             nonrobust
==============================================================================