I get different values of the importances when I use model.feature_importances_ versus xgb.plot_importance(model).
Moreover, the numpy array feature_importances do not directly correspond to the indexes that are returned from the plot_importance function.
Here is what the plot looks like:
But this is the output of model.feature_importances_ gives entirely different values:
array([ 0. , 0. , 0. , 0. , 0. ,
0. , 0.00568182, 0. , 0. , 0. ,
0.13636364, 0. , 0. , 0. , 0.01136364,
0. , 0. , 0. , 0. , 0.07386363,
0.03409091, 0. , 0.00568182, 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0.00568182, 0. , 0. , 0. ,
0. , 0. , 0.00568182, 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0.01704546, 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0.05681818, 0.15909091, 0.0625 , 0. ,
0. , 0. , 0.10227273, 0. , 0.07386363,
0.01704546, 0.05113636, 0.00568182, 0. , 0. ,
0.02272727, 0. , 0.01136364, 0. , 0. ,
0.11363637, 0. , 0.01704546, 0.01136364, 0. ,
0. , 0. , 0. , 0. , 0. ,
0. , 0. , 0. ], dtype=float32)
If I just try to grab Feature 81 (model.feature_importances_[81]), I get:0.051136363. However model.feature_importances_.argmax() returns 72.
Any idea why these two methods give me qualitatively different results?
