302 - Tuning deep learning hyperparameters using GridSearchCV
Автор: DigitalSreeni
Загружено: 2023-04-12
Просмотров: 12936
Tuning deep learning hyperparameters using Gridsearch
Code generated in the video can be downloaded from here:
https://github.com/bnsreenu/python_fo...
All other code:
https://github.com/bnsreenu/python_fo...
The grid search provided by GridSearchCV exhaustively generates candidates from a grid of parameter values specified with the param_grid parameter.
The GridSearchCV instance when “fitting” on a dataset, all the possible
combinations of parameter values are evaluated, and the best combination is retained.
cv parameter can be defined for the cross-validation splitting strategy.
GridSearch is designed to work with models from sklearn. But, we can also use it to tune deep learning hyper parameters - at least for keras models.
Wisconsin breast cancer example
Dataset link: https://www.kaggle.com/datasets/uciml...
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