Layer provides a declarative way of Hyperparameter Tuning. In this example, we will tune the parameters of Titanic Survival Model to find the best configuration. We will see how we can use different search algorithms: Random, Bayesian, Manual and Grid.
In this project, you will find the same dataset and featuresets we have developed for the Titanic Survival Model but also four different models each tuned with different search algorithms.
- Hyperparameter tuning with four different search algorithms:
To check out the Hyperparameter Tuning example, run:
To build the project: