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Hands-On Automated Machine Learning
book

Hands-On Automated Machine Learning

by Sibanjan Das, Umit Mert Cakmak
April 2018
Beginner to intermediate content levelBeginner to intermediate
282 pages
6h 52m
English
Packt Publishing
Content preview from Hands-On Automated Machine Learning

Bayesian-based hyperparameter tuning

There are a couple of approaches to be used when it comes to model-based hyperparameter tuning and these approaches come together under Sequential Model-based Global Optimization (SMBO).

When you think about GridSearchCV or RandomizedSearchCV, you may rightfully feel that the way they cross validate hyperparameters is not very smart. Both pre-define sets of hyperparameters to be validated during training time and are not designed to benefit from the information that they might get during training. If you could find a way to learn from previous iterations of hyperparameter validation based on model performance, then you would have an idea about which hyperparameter set is likely to give a better performance ...

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Publisher Resources

ISBN: 9781788629898Supplemental Content