Variable Importance Analysis in Python

When dealing with machine learning problems, sometimes one has to face a huge dataset with hundreds or thousands of features. Machine learning relies on these data to build models for prediction, more information the features contain, more easier to train a good model. However, these variables also contain noise, and most of them might be anonymous or formatted by some kind of hash process due to privacy issue or confidential reasons. So it's hard to figure out the physical meaning and explain the correlation between these variables. Even we could know all variables' meanings, it's still difficult to determine which are more essential than others.