I have a dataset with 5K records focused on binary classification problem. I have more than 60 features in my dataset. When I used
Xgboost, I got the below
Feature Importance plot. However I am not sure how to find out whether all of these are informative?
1) Yes, I can select top 15/20/25 etc. But is that how it is done? Is there any minimum
F-score that we ought to look for?
2) Or is it like I select top 10 features, check for accuracy and again add 2-3 features in every round and verify accuracy manually. Is this how it is done?
3) How would you people go about it? I tried with full dataset, the accuracy is only about 86%. when I tried with 15-20 features, it's only about 84. So manual feature selection is the only way to improve further?
Can you help me please?