EBM (Explainable Boosting Machines)

I work in finance (where GBDTs work well and interpretability is beneficial). Came across EBMs today. They claim performance matches XGB/Cat/LightGBM but has precise feature importance for every prediction and in some implementations the magnitude of individual feature influences can actually be tweaked by the user post-fit. Seems quite useful if my understanding is correct.

https://interpret.ml/docs/ebm.html

Anybody worked with these? What’s your experience been?

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