title: feature selection using logistic regression
body: <p>I am performing feature selection ( on a dataset with 1,930,388 rows and 88 features) using Logistic Regression. If I test the model on held-out data, the accuracy is just above 60%. The response variable is equally distributed. My question is, if the model's performance is not good, can I consider the features that it gives as actual important features? Or should I try to improve the accuracy of the model though my end-goal is not to improve the accuracy but only get important features</p>