I am wondering if you we can get the feature importance as a list of columns instead of a plot. This is what I have
xg_reg = xgb.train(params=params, dtrain=data_dmatrix, num_boost_round=10) import matplotlib.pyplot as plt xgb.plot_importance(xg_reg) plt.rcParams['figure.figsize'] = [5,5] plt.show()
Which gives me this plot
I would like to instead just get a list of the top features since I have over 800 different features.
You can use
xgb.get_score(). Here are a number of examples: How to get feature importance in xgboost?