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SGBT ensemble orchestrator – the core boosting loop.
Implements Streaming Gradient Boosted Trees (Gunasekara et al., 2024): a sequence of boosting steps, each owning a streaming tree and drift detector, with automatic tree replacement when concept drift is detected.
§Algorithm
For each incoming sample (x, y):
- Compute the current ensemble prediction:
F(x) = base + lr * Σ tree_s(x) - For each boosting step
s = 1..N:- Compute gradient
g = loss.gradient(y, current_pred) - Compute hessian
h = loss.hessian(y, current_pred) - Feed
(x, g, h)to trees(which internally uses weighted squared loss) - Update
current_pred += lr * tree_s.predict(x)
- Compute gradient
- The ensemble adapts incrementally, with each tree targeting the residual of all preceding trees.
Modules§
- adaptive
- Adaptive learning rate wrapper for SGBT ensembles.
- adaptive_
forest - Adaptive Random Forest (ARF) for streaming classification.
- bagged
- Bagged SGBT ensemble using Oza online bagging (Poisson weighting).
- config
- SGBT configuration with builder pattern and full validation.
- distributional
- Distributional SGBT – outputs Gaussian N(μ, σ²) instead of a point estimate.
- lr_
schedule - Learning rate scheduling for streaming gradient boosted trees.
- moe
- Streaming Mixture of Experts over SGBT ensembles.
- moe_
distributional - Streaming Mixture of Experts over Distributional SGBT ensembles with shadow expert competition.
- multi_
target - Multi-target regression via parallel SGBT ensembles.
- multiclass
- Multi-class classification via one-vs-rest SGBT committees.
- quantile_
regressor - Non-crossing multi-quantile regression via parallel SGBT ensembles.
- replacement
- TreeSlot: warning/danger/swap lifecycle for tree replacement.
- stacked
- Polymorphic model stacking meta-learner for streaming ensembles.
- step
- Single boosting step: owns one tree + drift detector + optional alternate.
- variants
- SGBT computational variants (Gunasekara et al., 2024).
Structs§
- SGBT
- Streaming Gradient Boosted Trees ensemble.
Type Aliases§
- DynSGBT
- Type alias for an SGBT model using dynamic (boxed) loss dispatch.