Search spaces

A search space describes the values HyperOptimizer is allowed to try. Good search spaces are small enough to learn from and broad enough to discover better configurations.

What belongs in a search space

Tune parameters that materially affect your objective and can be changed at runtime. Keep fixed infrastructure details, secrets, and environment-specific settings outside the search space.

Good candidates

Strategy thresholds, lookback windows, learning rates, batch sizes, timeframes, and objective weights.

Usually fixed

Database URLs, API keys, container image tags, model checkpoints, and credentials. Pass those as env vars or bake them into the image.

Be careful

Parameters that change runtime by orders of magnitude or make many trials invalid.

Parameter types in the dashboard

The create-experiment wizard uses these types (stored API values in parentheses):

Dashboard label	Stored type	Description
Whole number	int	Countable values such as --hpo-lookback-window=50. Optional custom step; log sampling available.
Continuous value	double	Continuous values such as --hpo-risk-multiplier=1.4. Optional step and log sampling.
Fixed choices	categorical	Discrete options such as --hpo-timeframe=5m.
True / false	categorical (true,false)	Feature flags such as --hpo-use-trailing-stop=true.

Naming parameters

Use stable kebab-case slugs in the dashboard. HyperOptimizer passes them with the --hpo- prefix by default (or plain -- if you switch flag mode). Most CLI parsers convert dashes to underscores in code.

--hpo-lookback-window=50
--hpo-risk-multiplier=1.4
--hpo-timeframe=5m

See CLI parameters for plain flags and {{slug}} command templates.