17e6c7a78f
First 10 bars proved the env_step kernel produces actual_dir=Long for Long picks correctly at cold start. So the gate that turns 100% of Long/Short picks into actual_dir=Flat in val_dir_dist must activate LATER in the window — likely past the first chunk boundary. Extended sampling: first 10 bars, every 100 bars to 1000, every 1000 bars to 10000, every 10000 bars throughout. Also adds a "mismatch" trigger that fires when picked dir is Long/Short but actual_dir is not — every 137 bars to keep printf volume bounded. cash field added to spot capital drain or anomalous accumulation. 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;