What is the difference between GLM and Logit model with statsmodels?
GLM is a generalized linear model and Logit Model is specific to models with binary classification. While using GLM model you have to mention the parameter family which can be binomial (logit model), Poisson etc. This parameter is not required in Logit model as its only for binary output. The difference in the output can be because of regularization parameters.
Can anyone please explain the difference between generalized linear model and logistic regression model table with statsmodels. Why do I get different results with both the models while performing logistic regression??