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HyperGBM is a full pipeline automated machine learning (AutoML) toolkit designed for tabular data, covering data cleaning, preprocessing, feature generation, model selection, and hyperparameter optimization. It optimizes the entire ML pipeline using reinforcement learning, Monte Carlo Tree Search, and evolutionary algorithms, and supports gradient boosting models like XGBoost, LightGBM, and Catboost.
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