60804788eb
Rewrite the three sp5_budget_c51/cql/ens registry descriptions to be
accurate at HEAD aa2854017: replace present-tense "driven by"/"no longer
writes" with future-tense "will be driven by"/"will stop writing", replace
non-existent C51_BOOTSTRAP_BUDGET/CQL_BOOTSTRAP_BUDGET/ENS_BOOTSTRAP_BUDGET
named constants with their actual anonymous .max() literal line references,
and apply the "(Pearl 2 will stop writing...)" parenthetical uniformly to all
three slots (cql was missing it). Audit doc T2 bullet updated accordingly.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ml
10-model ML ensemble for the Foxhunt HFT system, built on Candle v0.9.1.
Models
- DQN (Rainbow) — deep Q-network with prioritized replay, dueling heads, noisy nets
- PPO — proximal policy optimization with GAE, LSTM policies, clip-higher
- TFT — temporal fusion transformer for multi-horizon forecasting
- Mamba2 — state space model for sequence prediction
- Liquid Networks — biologically inspired networks for non-stationary data
- TLOB — transformer-based limit order book analysis
- KAN — Kolmogorov-Arnold networks
- xLSTM — extended LSTM architecture
- TGGN — temporal graph neural network
- Diffusion — diffusion-based generative model
Key Modules
ensemble— model ensemble coordination and confidence aggregationhyperopt— PSO-based hyperparameter optimization with per-model adapterstrainers— unified training loops (DQN, PPO, supervised)inference—InferenceAdaptertrait for predictioncheckpoint— model checkpointing and restorationevaluation— walk-forward evaluation pipeline
Usage
use ml::dqn::DQN;
use ml::ppo::PpoTrainer;