`optimizableVariable` — Create Bayesian optimization variable metadata.

optimizableVariable(Name,Range) constructs a host metadata object describing a variable for Bayesian optimization workflows.

Syntax

v = optimizableVariable(Name, Range)
v = optimizableVariable(Name, Range, Name, Value)

The variable name must be a nonempty text scalar.
Numeric ranges must contain exactly two finite, increasing bounds and default to Type real.
Type accepts real, integer, and categorical; integer ranges must use whole-number bounds.
Categorical ranges are accepted as string arrays, scalar strings with explicit Type categorical, or cell arrays of text scalars and must be nonempty and unique.
Transform accepts none and log; log transforms require positive real lower bounds or nonnegative integer lower bounds and are not accepted for categorical variables.
Optimize accepts scalar logical values and defaults to true.
The result is an optimizableVariable compatibility object with Name, Range, Type, Transform, and Optimize properties.

optimizableVariable constructs host metadata for bayesopt; gpuArray range and option inputs are gathered before validation.

v = optimizableVariable("depth", [1 10])

Expected output:

optimizableVariable compatibility object.

v = optimizableVariable("kernel", ["linear" "rbf"], "Type", "categorical")

Expected output:

optimizableVariable compatibility object.

Open a RunMat example with live inputs, then ask the agent to explain how optimizableVariable changes the result.

Run a small optimizableVariable example, explain the result, then change one input and compare the output.

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