kumulant

DiagonalRegression

@Serializable
@SerialName(value = "DiagonalRegression")
data class DiagonalRegression(val featureSize: Int, val priorPrecision: Double = 1.0, val learningRate: ScalarExpr = ConstantRate(1.0), val penalty: Penalty = Penalty.None, val link: Link = Link.Identity) : RegressionStatSpec<DiagonalRegressionResult> (source)

Spec for DiagonalRegressionStat: factorised-Gaussian posterior with per-coordinate precision.

Constructors

DiagonalRegression

constructor(featureSize: Int, priorPrecision: Double = 1.0, learningRate: ScalarExpr = ConstantRate(1.0), penalty: Penalty = Penalty.None, link: Link = Link.Identity)(source)

Properties

featureSize

Number of input features.

learningRate

Per-step learning rate.

penalty

Gradient-step regulariser.

priorPrecision

Initial per-coordinate precision (inverse variance) seeded into every weight.