I'm trying to use eli5.show_prediction to explain feature importance at the record level. Below is part of the results I'm getting.
The raw score value shown below is -0.329, which corresponds to probability value exp(-0.329)/(exp(-0.329) + 1) = 0.418484. However, the probability I calculated for this record using my XGB model turns out to be 0.8953. Is this difference expected? I used weights when building my XGB model, I wonder whether that's the issue.
Additionally, I used 100~ish features in my XGB model, but the eli5.show_prediction only shows feature importance of the top 70. What should I do in order to make the program output feature importance for all ~100 features?
Below is the output given by .show_prediction currently:
_y (score -0.329) top features
Contribution Feature Value
0.126 feature 1 1844
0.126 feature 3 100
0.108 feature 10 47
0.086 feature 100 100
0.057 feature 20 0
0.043 feature 5 47
0.039 bias 1
0.038 feature 56 0
... more results...