title: How to find the importance of the features for a logistic regression model?
body: <p>I have a binary prediction model trained by logistic regression algorithm. I want know which features(predictors) are more important for the decision of positive or negative class. I know there is <code>coef_</code> parameter comes from the scikit-learn package, but I don't know whether it is enough to for the importance. Another thing is how I can evaluate the <code>coef_</code> values in terms of the importance for negative and positive classes. I also read about standardized regression coefficients and I don't know what it is.</p>
  
  <p>Lets say there are features like size of tumor, weight of tumor, and etc to make a decision for a test case like malignant or not malignant. I want to know which of the features are more important for malignant and not malignant prediction. Does it make sort of sense?</p>