Files
foxhunt/crates/ml
jgrusewski 93e4185fa5 feat: rank-preserving signed reward standardization — SNR 0.001→0.5
r_shaped = sign(r) * rank(|r|) * std_ema. Counting-sort rank within
batch gives outlier-resistant, scale-free normalization. Sign preserved
for absolute direction. std_ema rescales to original magnitude range.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 21:52:52 +02:00
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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 aggregation
  • hyperopt — PSO-based hyperparameter optimization with per-model adapters
  • trainers — unified training loops (DQN, PPO, supervised)
  • inferenceInferenceAdapter trait for prediction
  • checkpoint — model checkpointing and restoration
  • evaluation — walk-forward evaluation pipeline

Usage

use ml::dqn::DQN;
use ml::ppo::PpoTrainer;