[Project] PerpetualBooster v1.9.4 - a GBM that skips the hyperparameter tuning step entirely. Now with drift detection, prediction intervals, and causal inference built in.

Summary

PerpetualBooster v1.9.4 is an innovative gradient boosting machine that skips the hyperparameter tuning step by using a single budget parameter. The new version also includes features for drift detection, prediction intervals, and causal inference, making the model easy and efficient to train and generalize.