I have one dataset, and decided to use XGBClassifier to get a variable importance plot from it.
I was a little surprised that some features that I assumed were insightful had no appreciable value. With this in mind, I used an sklearn RandomForestClassifier to create another variable importance plot.
To my surprise the two were very different! Many variables that appear on one don't appear on the other.
I used as similar parameters as I could, between the two models.
Here's what they look like to give a general idea:
Has anyone had this similar experience, and if so, what kinds of reasoning for this might there be? It's a little frightening to think that many Kagglers and others really depend on these plots and to see that they can vary so much...makes me wonder.