KSLCore/ksl.simopt.solvers.algorithms.bo/SurrogateModelIfc

SurrogateModelIfc

A surrogate model that is fit to noisy observations and predicts a posterior mean and variance at an arbitrary input point. Bayesian optimization optimizes a cheap acquisition function over this surrogate rather than over the expensive simulation.

Inheritors

GaussianProcessModel

Types

Prediction

data class Prediction(val mean: Double, val variance: Double)

A posterior prediction: the mean and (non-negative) variance, with a convenience standardDeviation.

Functions

fit

abstract fun fit(points: List<DoubleArray>, means: DoubleArray, noiseVars: DoubleArray)

Fits the surrogate to the supplied observations.

predict

abstract fun predict(x: DoubleArray): SurrogateModelIfc.Prediction

Predicts the posterior mean and variance at x. The model must have been fit first.