Hyperparameter optimization
In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts.
Hyperparameter optimization - Wikipedia Jump to content From Wikipedia, the free encyclopedia Process of finding the optimal set of variables for a machine learning algorithm In machine learning , hyperparameter optimization [ 1 ] or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts. [ 2 ] [ 3 ] Hyperparameter optimization determines the set of hyperparameters that yields an optimal model which
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