PlattCalibratorStat
Online Platt scaling: fits a one-feature logistic regression sigmoid(slope * rawScore + intercept) over paired (rawScore, label) observations where label is in {0, 1}. Use to fix the calibration of a classifier whose probability output is poorly aligned with the empirical positive rate.
Internally wraps a StochasticRegressionStat with featureSize = 1 and Link.Logit. The runtime cost matches a one-dimensional GLM-SGD update per observation.
Use cases: post-hoc calibration of tree / SVM / naive-Bayes outputs; pair with ReliabilityStat to monitor the gap before and after applying the learned mapping.
Memory: O(1); backed by StochasticRegressionStat.
Update: O(1) per observation.
Concurrency: Inherits StochasticRegressionStat's concurrency model.
Constructors
Properties
Functions
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.
Folds another Platt result into this one by reconstructing a StochasticRegressionStat snapshot from (slope, intercept, totalWeights) and delegating to the underlying merge.
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.
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.
PlattCalibratorStat
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:
Concurrency.None: single-threaded; no synchronisation. Cheapest path.
Concurrency.Relaxed: lock-free best-effort. Multi-cell stats (Welford-style MeanStat, VarianceStat, MomentsStat) may drift under contention but never throw.
Concurrency.Strict: serialised when needed for full correctness across coupled cells. Sketches always self-serialise; Welford stats lock per update.
Concurrency.HighWrite: optimised for many concurrent writers; JVM uses striped adders for naively additive stats.
Picked at construction; immutable after.
create
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.
merge
Folds another Platt result into this one by reconstructing a StochasticRegressionStat snapshot from (slope, intercept, totalWeights) and delegating to the underlying merge.
optimizer
Optimizer driving the underlying logistic regression.
read
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
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.