Archives for FLAML
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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Guide To Microsoft’s FLAML
The current data science scenario raises a big question: how and what to select as a machine learning model to predict all best. When selecting, we use conventional ways like hyperparameter tuning, GridSearchCV and Random search to choose the best-fit parameters. These conventional techniques help us a lot, but they are time-consuming, take high computation…
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