Known_Ad_5120 t1_isyq0pi wrote on October 19, 2022 at 5:54 PM Reply to [D] Simple Questions Thread by AutoModerator Feature Importance and Threshold Moving Problem Type : Binary Classification Dataset : Imbalanced Current sklearn pipeline uses XGBoost model and involves moving threshold from 0.5 to a considerably higher value like 0.8 - 0.9. Is it viable to use XGBoost's feature importance metrics for identifying the relevant features, if not what would be a better alternate? Permalink 2
Known_Ad_5120 t1_isyq0pi wrote
Reply to [D] Simple Questions Thread by AutoModerator
Feature Importance and Threshold Moving
Problem Type : Binary Classification
Dataset : Imbalanced
Current sklearn pipeline uses XGBoost model and involves moving threshold from 0.5 to a considerably higher value like 0.8 - 0.9.
Is it viable to use XGBoost's feature importance metrics for identifying the relevant features, if not what would be a better alternate?