A self-generalizing, hyperparameter-free gradient boosting machine

PerpetualBooster is a gradient boosting machine (GBM) algorithm which doesn't have hyperparameters to be tuned so that you can use it without needing hyperparameter optimization packages unlike other GBM algorithms. Similar to AutoML libraries, it has a budget parameter which ranges between (0, 1). Increasing the budget parameter increases predictive power of the algorithm and gives better results on unseen data.

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