kumulant
com.eignex.kumulant/schema/spec/RandomForestRegression

RandomForestRegression

@Serializable
@SerialName(value = "RandomForestRegression")
data class RandomForestRegression(val featureSize: Int, val splitCandidates: List<SerializableSplit>, val nbrTrees: Int = StatDefaults.FOREST_SIZE, val config: RegressionTreeConfig = RegressionTreeConfig(), val bagging: Boolean = StatDefaults.FOREST_BAGGING, val randomSeed: Int = StatDefaults.TREE_RANDOM_SEED, val leafArm: SeriesStatSpec<WeightedVarianceResult>? = null) : RegressionStatSpec<ForestRegressionResult> (source)

Spec for RandomForestRegressionStat: ensembled VFDT regression forest.

Constructors

RandomForestRegression

constructor(featureSize: Int, splitCandidates: List<SerializableSplit>, nbrTrees: Int = StatDefaults.FOREST_SIZE, config: RegressionTreeConfig = RegressionTreeConfig(), bagging: Boolean = StatDefaults.FOREST_BAGGING, randomSeed: Int = StatDefaults.TREE_RANDOM_SEED, leafArm: SeriesStatSpec<WeightedVarianceResult>? = null)(source)

Properties

bagging

val bagging: Boolean(source)

Oza & Russell Poisson(1) per-tree reweighting.

config

val config: RegressionTreeConfig(source)

RegressionTree growth tunables (mtry defaults to ceil(sqrt(p)) when null).

featureSize

val featureSize: Int(source)

Number of input features.

leafArm

val leafArm: SeriesStatSpec<WeightedVarianceResult>?(source)

Per-leaf accumulator recipe; null uses the stat's default leaf arm.

nbrTrees

val nbrTrees: Int(source)

Trees in the forest.

randomSeed

val randomSeed: Int(source)

PRNG seed shared across trees.

splitCandidates

val splitCandidates: List<SerializableSplit>(source)

Candidate split pool.