profitable-expert-advisor/ai/xauusd_h1/README.md

XAUUSD H1 — ONNX action model

Same pipeline as ../xauusd_m15, but H1 bars, H1-scaled label windows (~wall-clock parity with M15 defaults), and XAUUSD_H1_ActionEA.mq5.

Label scaling (vs M15)

M15 (bars)	Wall time	H1 (bars)
horizon 32	~8 h	8
local 24	~6 h	6
pullback 20	~5 h	5

Setup

1. MT5: XAUUSD visible; download H1 history.
2. Python:

cd ai/xauusd_h1
pip install -r requirements.txt
python main.py

Env: XAU_SYMBOL, XAU_H1_LOOKBACK (default 48, must match EA InpLookback), XAU_EPOCHS, XAU_BATCH, SESSION_HOUR_OFFSET.

3. Copy models/XAUUSD_H1_action.onnx next to XAUUSD_H1_ActionEA.mq5 (for #resource embed) or adjust include path per your workflow.
4. Compile EA on H1 chart; paste 24 floats into InpFeatMinStr / InpFeatMaxStr from training stdout.

Files

File	Role
main.py	MT5 H1 fetch, train, XAUUSD_H1_action.onnx + meta
labeling.py	compute_action_labels (H1 default horizons)
features.py	24-dim features (same order as M15 EA)
XAUUSD_H1_ActionEA.mq5	Inference + trading
XAUUSD_H1_ActionEA_optimize.set	Tester optimization skeleton

Feature semantics: ../xauusd_m15/FRONTLINE_RSI_INTEGRATION.md.

ONNX

• Input: [1, lookback, 24] float32, row 0 = newest bar.
• Output: [1, 5] softmax.

Research tooling — not investment advice.