trader-train

Train neural prediction models using neural-trader's ML engine. Steps: 1. Ensure neural-trader is available: `npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-trader` 2. Train the specified model: ```bash npx neural-trader --model lstm --symbol TICKER --confidence 0.95 npx neural-trader --model transformer --symbol TICKER --predict npx neural-trader --model nbeats --symbol TICKER --decompose ``` 3. Review training output: loss curves, validation metrics, prediction accuracy 4. Generate predictions with confidence intervals: ```bash npx neural-trader --model MODEL --symbol TICKER --predict --horizon 5d ``` 5. Compare model performance across types: ```bash npx neural-trader --model-compare --symbol TICKER --models "lstm,transformer,nbeats" ``` 6. Store model results (canonical `trading-analysis` namespace per ADR-126 Phase 1 — was previously stored to undeclared `trading-models`): `mcp__plugin_ruflo-core_ruflo__memory_store({ key: "model-MODEL-TICKER-DATE", value: "TRAINING_RESULTS", namespace: "trading-analysis" })` 7. Train SONA on model outcomes: `mcp__plugin_ruflo-core_ruflo__neural_train({ patternType: "trading-model", epochs: 10 })`