Main take-away

Main take-away#

Wrap-up#

  • Hyperparameters have an impact on the models’ performance and should be wisely chosen;

  • The search for the best hyperparameters can be automated with a grid-search approach or a randomized search approach;

  • A grid-search can be computationally expensive and becomes less attractive as the number of hyperparameters to explore increases. Moreover, the combinations are sampled on a fixed, regular grid.

  • A randomized-search allows exploring within a fixed budget, even as the number of hyperparameters increases. In this case, combinations can be sampled either on a regular grid or from a given distribution.

To go further#

You can refer to the following scikit-learn examples which are related to the concepts approached during this module:

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