b14c60d4cc
- Raise eval_softmax_temp lower bound from 0.01 to 0.1 (log scale) to prevent near-greedy collapse in hyperopt walk-forward eval. Temps below 0.05 produced degenerate 1-trade trials even with softmax sampling. - Mount MinIO CA cert in CI compile pods and append to system trust store so sccache S3 backend can verify MinIO's self-signed TLS certificate. - Add openssh-client to ci-builder-cpu Dockerfile (missing, broke git clone over SSH). - Bump MinIO memory limits from 512Mi to 2Gi (OOMKilled under load). 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;