kumulant

DecisionTreeClassifierStat

class DecisionTreeClassifierStat(val featureSize: Int, val numClasses: Int, val splitCandidates: List<Split>, val config: ClassificationTreeConfig = ClassificationTreeConfig(), val concurrency: Concurrency = Concurrency.None, leafArmFactory: () -> SeriesStat<ClassCountsResult> = { ClassCountsStat(numClasses, concurrency) }, randomSeed: Int = 0) : RegressionStat<TreeClassificationResult> (source)

Online VFDT decision-tree classifier; the classification counterpart of DecisionTreeRegressionStat. Each leaf carries a ClassCountsResult (per-class weighted counts); splits fire when a candidate beats the runner-up by the Hoeffding bound on Gini reduction or information gain.

Input is fed through RegressionStat: x is the feature vector, y is the class index in [0, numClasses) (truncated via toInt()).

Constructors

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constructor(featureSize: Int, numClasses: Int, splitCandidates: List<Split>, config: ClassificationTreeConfig = ClassificationTreeConfig(), concurrency: Concurrency = Concurrency.None, leafArmFactory: () -> SeriesStat<ClassCountsResult> = { ClassCountsStat(numClasses, concurrency) }, randomSeed: Int = 0)

Properties

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open override val concurrency: Concurrency

The thread-safety contract this stat was constructed with. Each stat picks the cell-encoding and lock strategy that honours this contract for its mathematical structure:

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Tunables shared with the underlying ClassificationTree.

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open override val featureSize: Int

Number of features expected in x on each update. Mismatched lengths throw.

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Number of classes; the input y must round to [0, numClasses).

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Candidate splits considered at every audit leaf.

Functions

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open override fun create(concurrency: Concurrency? = null): DecisionTreeClassifierStat

Spawn a fresh accumulator with the same configuration. Optionally override the Concurrency; useful for materialising a wire spec at a different concurrency level than the source.

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open override fun merge(values: TreeClassificationResult)

Fold another accumulator's snapshot into this one. The unit of merge is the immutable Result; not a live Stat; which is what lets the merge cross a process boundary. Many workers track slices of the same stream, call read periodically, ship snapshots to a coordinator, and the coordinator merges them in.

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open override fun read(timestampNanos: Long = currentTimeNanos()): TreeClassificationResult

Materialise the current state as an immutable Result. Reads never mutate, so the caller can read as often as it likes without affecting the stream.

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open override fun reset()

Reset the stat to its prior-seeded baseline. Equivalent to constructing a fresh stat with the same configuration, but in place; keeps the same Concurrency and any per-stat tunables.

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Live underlying classification tree. Use for inspection / pretty-printing.

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open fun update(x: VectorView, y: Double, weight: Double = 1.0)

Record an (x, y) observation with the given weight at the current time.

open fun update(x: DoubleArray, y: Double, weight: Double = 1.0)

Convenience overload that wraps x as a DenseVector.

open fun update(x: DoubleArray, y: Double, timestampNanos: Long, weight: Double = 1.0)

Timestamped convenience overload that wraps x as a DenseVector.

open override fun update(x: VectorView, y: Double, timestampNanos: Long, weight: Double = 1.0)

Record an (x, y) observation at timestampNanos with the given weight.

DecisionTreeClassifierStat

constructor(featureSize: Int, numClasses: Int, splitCandidates: List<Split>, config: ClassificationTreeConfig = ClassificationTreeConfig(), concurrency: Concurrency = Concurrency.None, leafArmFactory: () -> SeriesStat<ClassCountsResult> = { ClassCountsStat(numClasses, concurrency) }, randomSeed: Int = 0)(source)

concurrency

open override val concurrency: Concurrency(source)

The thread-safety contract this stat was constructed with. Each stat picks the cell-encoding and lock strategy that honours this contract for its mathematical structure:

Picked at construction; immutable after.

config

Tunables shared with the underlying ClassificationTree.

create

open override fun create(concurrency: Concurrency? = null): DecisionTreeClassifierStat(source)

Spawn a fresh accumulator with the same configuration. Optionally override the Concurrency; useful for materialising a wire spec at a different concurrency level than the source.

The returned stat is independent: its state starts at the configured baseline, not at the source's current state. Each modality subtype narrows the return type so chaining doesn't lose the modality.

featureSize

open override val featureSize: Int(source)

Number of features expected in x on each update. Mismatched lengths throw.

merge

open override fun merge(values: TreeClassificationResult)(source)

Fold another accumulator's snapshot into this one. The unit of merge is the immutable Result; not a live Stat; which is what lets the merge cross a process boundary. Many workers track slices of the same stream, call read periodically, ship snapshots to a coordinator, and the coordinator merges them in.

Most stat families implement merge exactly (Chan-style parallel formulas for Welford, cell-wise additions for histograms, cell-wise max for HLL). SGD-based regressors merge approximately; they have no second-moment information for the principled combine. Each stat's KDoc documents its merge semantics.

numClasses

Number of classes; the input y must round to [0, numClasses).

read

open override fun read(timestampNanos: Long = currentTimeNanos()): TreeClassificationResult(source)

Materialise the current state as an immutable Result. Reads never mutate, so the caller can read as often as it likes without affecting the stream.

Snapshot consistency depends on the configured Concurrency. Under Concurrency.Strict / Concurrency.HighWrite a read locks against writers so coupled cells stay consistent. Under Concurrency.Relaxed the cells race and the snapshot may drift by ULPs of the workload under heavy contention; the drift is bounded and the read never throws.

timestampNanos is the read timestamp. Stats that don't care about time silently drop it; stats that do (rates, decay families, recency, windowed wrappers) use it as the ordering signal.

reset

open override fun reset()(source)

Reset the stat to its prior-seeded baseline. Equivalent to constructing a fresh stat with the same configuration, but in place; keeps the same Concurrency and any per-stat tunables.

splitCandidates

Candidate splits considered at every audit leaf.

tree

Live underlying classification tree. Use for inspection / pretty-printing.

update

open override fun update(x: VectorView, y: Double, timestampNanos: Long, weight: Double = 1.0)(source)

Record an (x, y) observation at timestampNanos with the given weight.