Advanced Examples

Advanced Examples

These notebooks showcase more specialized and advanced use cases in BoFire. These examples are not necessarily better strategies, but represent more complex uses of components within the library.

Available Tutorials

Custom SOBO

Create custom single-objective Bayesian optimization strategies.

Desirability Objectives

Working with desirability functions for multi-criteria optimization.

Genetic Algorithm

Using genetic algorithms for optimization in BoFire.

Merging Objectives

Techniques for combining multiple objectives in optimization.

Multifidelity Bayesian Optimization

Leveraging multiple fidelity levels for efficient optimization.

Objectives on Inputs

Defining optimization objectives directly on input parameters.

Random Forest in BoFire

Using Random Forest as a surrogate model instead of Gaussian Processes.

Transfer Learning BO

Applying transfer learning techniques to Bayesian optimization.