kumulant
com.eignex.kumulant/schema/spec/BayesianRegression

BayesianRegression

@Serializable
@SerialName(value = "BayesianRegression")
data class BayesianRegression(val featureSize: Int, val priorVariance: Double = StatDefaults.BAYESIAN_REGRESSION_PRIOR_VARIANCE, val link: Link = StatDefaults.regressionLink, val priorMean: ContiguousVector? = null, val priorCovariance: DenseMatrix? = null) : RegressionStatSpec<PrecisionRegressionResult> (source)

Spec for BayesianRegressionStat: Gaussian linear regression with a configurable prior.

Constructors

BayesianRegression

constructor(featureSize: Int, priorVariance: Double = StatDefaults.BAYESIAN_REGRESSION_PRIOR_VARIANCE, link: Link = StatDefaults.regressionLink, priorMean: ContiguousVector? = null, priorCovariance: DenseMatrix? = null)(source)

Properties

featureSize

val featureSize: Int(source)

Number of input features.

priorCovariance

val priorCovariance: DenseMatrix?(source)

Prior coefficient covariance; null uses priorVariance times the identity.

priorMean

val priorMean: ContiguousVector?(source)

Prior coefficient mean; null uses the zero vector.

priorVariance

val priorVariance: Double(source)

Isotropic prior variance applied to every coefficient.