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Feature Iteration Run #1814: zz_sylvain

Status: completed | Started: 2026-10-03 13:11:28 | Ended: 2026-10-03 13:12:11

📊 Iterations

Iter Y Label Model Warm Proxy Parent FS Feature DSL DSL Valid Baseline PF Modified PF Scalar Score t-stat p-value Cohen's d Result Reason
1 C8 gradient_boosting — ✅ #1748 k_iter1_k_mom10_atrnorm_volratio mom_norm = ta.mom(close, 10) / close at… ❌ 1.612 0.000 0.0000 0.000 1.000 0.000 ❌ REJECT 1-trial proxy PF=0.000 < 0.95, no improvement expected

📄 Report Markdown

# AUTOLOOP: zz_sylvain (1 iterations)

> **Phase**: Y4.7 Option B (DSL → Python code → FeatureSet candidate)
> **Target indicator**: zz_sylvain
> **Base feature_set_id**: 1748
> **Claim**: (default) Propose a new k_* feature that improves risk-adjusted returns
> **Objective mode**: scalarize
> **Metrics**: ['profit_factor', 'sharpe_ratio', 'win_rate', 'max_drawdown', 'test_accuracy']
> **Total duration**: 42.30s
> **Total accepted**: 0
> **Total rejected**: 1

## Iterations 詳情

### Iteration 1
- DSL: `mom_norm = ta.mom(close, 10) / close
atr_n = ta.atr(high, low, close, 14) / close
vol_r = volume / ta.sma(volume, 20)
mom_norm = mom_norm / (1 + atr_n)
mom_vol = mom_norm * vol_r
mom_vol` (feature=k_iter1_k_mom10_atrnorm_volratio)
- DSL valid: False
- FeatureSet candidate id: 1818
- baseline PF: 1.612 → modified PF: 0.000
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: 1-trial proxy PF=0.000 < 0.95, no improvement expected

📊 Multi-Objective Metrics

Iteration 1: k_iter1_k_mom10_atrnorm_volratio

Y Label: C8 | Parent FS: #1748

Objective mode: single

Scalar score: 0.0000

📁 Offline Report

Markdown backup: reports/autoloop/zz_sylvain/20261003_211211.md