FLAML is an open-source automated python machine learning library that leverages the structure of the search space in search tree algorithmic problems and is designed to perform efficiently and robustly without relying on meta-learning, unlike traditional Machine Learning algorithms. To choose a search order optimized for both cost and error and it iteratively decides the learner, hyperparameter, sample size and resampling strategy while leveraging their compound impact on both cost and error of the model as the search proceeds.

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