Package-level declarations

Functions

fun Hyperparameters.bayes(maxTrials: Int = 50, initialTrials: Int = -1, maximize: Boolean = true, acquisition: BayesianOptimization.Acquisition = BayesianOptimization.Acquisition.EXPECTED_IMPROVEMENT, exploration: Double = 0.01, kernel: MercerKernel<DoubleArray> = MaternKernel(1.0, 2.5), objective: (Properties) -> Double): BayesianOptimization.Result

Executes Bayesian hyperparameter optimization.

gridSequence

fun Hyperparameters.gridSequence(): Sequence<Properties>

Returns all grid search configurations as a Kotlin sequence.

hyperparameters

fun hyperparameters(init: Hyperparameters.() -> Unit): Hyperparameters

Creates and configures a new hyperparameter search space using builder DSL.

randomSequence

fun Hyperparameters.randomSequence(n: Int): Sequence<Properties>

Returns n randomly sampled configurations as a Kotlin sequence.