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Known_Ad_5120 t1_isyq0pi wrote

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?

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