Feature Iteration Run #677: zz_sylvain
Status: completed | Started: 2026-07-18 11:25:30 | Ended: 2026-07-18 11:27:45
⭐ Best Accepted Iteration
Iteration 3: k_high.pct_change(12) * i_rsi(k_close, 14) / (1 + atr_norm)…
baseline PF: 1.286 → modified PF: 1.321 | Cohen's d: 0.000 | p-value: 1.000
📊 Iterations
| Iter | Y Label | Model | Warm | Proxy | Parent FS | Feature | Baseline PF | Modified PF | Scalar Score | Result |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_1_3970a7 | 1.286 | 1.218 | -0.4217 | ❌ REJECT |
| 2 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_2_e7d4fd | 1.286 | 1.286 | 0.0000 | ❌ REJECT |
| 3 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_3_af0be3 | 1.286 | 1.321 | 0.2086 | ✅ ACCEPT |
📄 Report Markdown
# AUTOLOOP: zz_sylvain (3 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**: 134.33s
> **Total accepted**: 1
> **Total rejected**: 2
## Iterations 詳情
### Iteration 1
- DSL: `k_high.pct_change(12) * i_rsi(k_close, 14) * (1 - price_position) * (1 - dist_to_high) * k_momentum_pct_change / (1 + hl_range) / (1 + k_body_size_pct) / (1 + k_consecutive_shrink)` (feature=k_loop_iter_1_3970a7)
- DSL valid: True
- FeatureSet candidate id: 853
- baseline PF: 1.286 → modified PF: 1.218
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: -0.4217
- accepted: False, reason: p=1.000 ≥ 0.05, cohens_d=0.000 ≤ 0.3
**Metrics summary:**
- profit_factor: baseline=1.286, modified=1.218, diff=-0.068
- sharpe_ratio: baseline=7.879, modified=6.309, diff=-1.570
- win_rate: baseline=0.553, modified=0.510, diff=-0.043
- max_drawdown: baseline=0.075, modified=0.073, diff=-0.002
- test_accuracy: baseline=0.986, modified=0.987, diff=0.000
### Iteration 2
- DSL: `k_high.pct_change(12) * i_rsi(k_close, 14) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high) * vol_ratio / (1 + hl_range)` (feature=k_loop_iter_2_e7d4fd)
- DSL valid: True
- FeatureSet candidate id: 854
- baseline PF: 1.286 → modified PF: 1.286
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: p=1.000 ≥ 0.05, cohens_d=0.000 ≤ 0.3
**Metrics summary:**
- profit_factor: baseline=1.286, modified=1.286, diff=0.000
- sharpe_ratio: baseline=7.879, modified=7.879, diff=0.000
- win_rate: baseline=0.553, modified=0.553, diff=0.000
- max_drawdown: baseline=0.075, modified=0.075, diff=0.000
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
### Iteration 3
- DSL: `k_high.pct_change(12) * i_rsi(k_close, 14) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high) * (1 - dist_to_low) / (1 + hl_range) * i_macd(k_close, 12, 26, 9)` (feature=k_loop_iter_3_af0be3)
- DSL valid: True
- FeatureSet candidate id: 855
- baseline PF: 1.286 → modified PF: 1.321
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.2086
- accepted: True, reason: accepted
**Metrics summary:**
- profit_factor: baseline=1.286, modified=1.321, diff=0.036
- sharpe_ratio: baseline=7.879, modified=8.697, diff=0.818
- win_rate: baseline=0.553, modified=0.520, diff=-0.033
- max_drawdown: baseline=0.075, modified=0.076, diff=0.001
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
📊 Multi-Objective Metrics
Iteration 1: k_loop_iter_1_3970a7
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: -0.4217
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.510 | -0.043 |
| max_drawdown | 0.075 | 0.073 | -0.002 |
| sharpe_ratio | 7.879 | 6.309 | -1.570 |
| profit_factor | 1.286 | 1.218 | -0.068 |
| test_accuracy | 0.986 | 0.987 | 0.000 |
Iteration 2: k_loop_iter_2_e7d4fd
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: 0.0000
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.553 | 0.000 |
| max_drawdown | 0.075 | 0.075 | 0.000 |
| sharpe_ratio | 7.879 | 7.879 | 0.000 |
| profit_factor | 1.286 | 1.286 | 0.000 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
Iteration 3: k_loop_iter_3_af0be3
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: 0.2086
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.520 | -0.033 |
| max_drawdown | 0.075 | 0.076 | 0.001 |
| sharpe_ratio | 7.879 | 8.697 | 0.818 |
| profit_factor | 1.286 | 1.321 | 0.036 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
📁 Offline Report
Markdown backup: reports/autoloop/zz_sylvain/20260718_192745.md