b57df47ddc
Create 8 missing READMEs (config, ctrader-openapi, market-data, ml-data, model_loader, risk-data, trading-data, training_uploader). Update 9 existing READMEs to standard template format. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
33 lines
1.1 KiB
Markdown
33 lines
1.1 KiB
Markdown
# ml
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10-model ML ensemble for the Foxhunt HFT system, built on Candle v0.9.1.
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## Models
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- **DQN (Rainbow)** — deep Q-network with prioritized replay, dueling heads, noisy nets
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- **PPO** — proximal policy optimization with GAE, LSTM policies, clip-higher
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- **TFT** — temporal fusion transformer for multi-horizon forecasting
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- **Mamba2** — state space model for sequence prediction
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- **Liquid Networks** — biologically inspired networks for non-stationary data
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- **TLOB** — transformer-based limit order book analysis
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- **KAN** — Kolmogorov-Arnold networks
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- **xLSTM** — extended LSTM architecture
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- **TGGN** — temporal graph neural network
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- **Diffusion** — diffusion-based generative model
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## Key Modules
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- `ensemble` — model ensemble coordination and confidence aggregation
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- `hyperopt` — PSO-based hyperparameter optimization with per-model adapters
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- `trainers` — unified training loops (DQN, PPO, supervised)
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- `inference` — `InferenceAdapter` trait for prediction
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- `checkpoint` — model checkpointing and restoration
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- `evaluation` — walk-forward evaluation pipeline
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## Usage
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```rust
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use ml::dqn::DQN;
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use ml::ppo::PpoTrainer;
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```
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