Feature Iteration Run #1323: zz_sylvain
Status: completed | Started: 2026-09-26 01:08:47 | Ended: 2026-09-26 01:09:05
📊 Iterations
📄 Report Markdown
# AUTOLOOP: zz_sylvain (2 iterations)
> **Phase**: Y4.7 Option B (DSL → Python code → FeatureSet candidate)
> **Target indicator**: zz_sylvain
> **Base feature_set_id**: 7
> **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**: 17.91s
> **Total accepted**: 0
> **Total rejected**: 2
## Iterations 詳情
### Iteration 1
- DSL: `` (feature=)
- DSL valid: True
- FeatureSet candidate id: None
- baseline PF: 0.000 → modified PF: 0.000
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: propose v4.2: LLM 回應 parse_failed — reject 該輪(不靜默落 stub)。
### Iteration 2
- DSL: `` (feature=)
- DSL valid: True
- FeatureSet candidate id: None
- baseline PF: 0.000 → modified PF: 0.000
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: propose v4.2: LLM 回應 parse_failed — reject 該輪(不靜默落 stub)。
📊 Multi-Objective Metrics
Iteration 1:
Y Label: C8 | Parent FS: #7
Objective mode: single
Scalar score: 0.0000
Iteration 2:
Y Label: C8 | Parent FS: #7
Objective mode: single
Scalar score: 0.0000
📁 Offline Report
Markdown backup: reports/autoloop/zz_sylvain/20260926_090905.md