UcbTreePosterior
data class UcbTreePosterior(val priorWeight: Double = 1.0, val priorVariance: Double = 1.0) : TreePosterior(source)
UCB-style score: mean + exploration * sqrt(variance / (totalWeights + priorWeight)). The sqrt(.) term is the leaf's standard error of the mean; the prior-weight floor keeps the bound finite at empty leaves.
Properties
Functions
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open override fun evaluate(snapshot: TreeRegressionResult, x: VectorView, rng: Random, exploration: Double = 1.0): Double
Score a query point x under the regression snapshot. exploration controls the posterior-variance scale (Thompson) or the UCB width (LinUcb-style); 0.0 collapses to the point estimate.
UcbTreePosterior
evaluate
open override fun evaluate(snapshot: TreeRegressionResult, x: VectorView, rng: Random, exploration: Double = 1.0): Double(source)
Score a query point x under the regression snapshot. exploration controls the posterior-variance scale (Thompson) or the UCB width (LinUcb-style); 0.0 collapses to the point estimate.
priorVariance
Prior variance used when the leaf has no signal yet.
priorWeight
Pseudo-count added to the leaf's totalWeights; floor for empty leaves.