fa8acef9e9
- Walk-forward CPU backtest was calling feature_vector_to_state() without OFI index, producing zero OFI features during evaluation while training had real OFI — creating a silent train/eval feature mismatch - Add convert_to_state_vec_with_ofi() public method on DQNTrainer - Add ofi_val_offset field to track training data length for OFI indexing - compute_validation_loss() now passes OFI index to validation states - Hyperopt CPU eval path now uses convert_to_state_vec_with_ofi() - Enable DSR (Differential Sharpe Ratio) by default in both config and GPU experience collector — aligns with hyperopt which always uses DSR - Fix ensemble adapter test to explicitly disable branching Co-Authored-By: Claude Opus 4.6 <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;