Facades

SMAC of course itself offers a lot of design choices, some of which are crucial to achieve peak performance. Luckily, often it is sufficient to distinguish between a few problem classes. To make the usage of SMAC as easy as possible, we provide several facades designed for these different use cases. Here we give some general recommendations on when to use which facade. These recommendations are based on our experience and technical limitations and is by far not intended to be complete:

	SMAC4BB	SMAC4HPO	SMAC4MF	SMAC4AC
# parameter	low	low/medium/high	low/medium/high	low/medium/high
Categorical hyperparameters	Supported	Supported	Supported	Supported
Conditional hyperparameters	Supported	Supported	Supported	Supported
Instances	No	None or CV	None or CV	Yes
Stochasticity	No	Supported	Supported	Supported
Objective	Any (except runtime)	e.g. validation loss	e.g. validation loss	Any
Multi-Fidelity	No	No	Yes	Yes
Search Strategy	Gaussian Process or GP-MCMC	Random Forest	Random Forest	Random Forest, Gaussian Process, GP-MCMC or Random

Note

The SMAC4MF facade is the closest implementation to BOHB.

Inheritance

Here we show the class inheritance of the different facades. Because SMAC4AC is the facade every other facade is inherited from, we recommend using SMAC4AC if a lot of flexibility is needed.

Class inheritance of the SMAC facades.

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