I have a binary prediction model trained by the logistic regression algorithm. I want to know which features(predictors) are more important for the decision of positive or negative class. I know there is a coef_ 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 coef_ values in terms of the importance of negative and positive classes. I also read about standardized regression coefficients and I don't know what it is.

Let's say there are features like the size of the 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?