Wednesday, May 2, 2018

machine learning, hyper parameters

hyper-parameters, such as partition data into training, validation, and testing, iteractions, in general have no fixed way to pick theoretically.

hyper-parameters are those that need to be fixed before learning started.

hyperparameter optimization may be done by compare a tuple of hyperparameters, based on a predefined loss function on dependent data.

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