Feature Iteration Run #711: zz_sylvain
Status: completed | Started: 2026-07-18 13:56:15 | Ended: 2026-07-18 13:59:54
⭐ Best Accepted Iteration
Iteration 1: k_high.pct_change(12) / (1 + atr_norm) * (1 - price_positio…
baseline PF: 1.286 → modified PF: 2.113 | 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_2_301c87 | 1.286 | 2.113 | 3.7086 | ✅ ACCEPT |
| 2 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_3_4e9c71 | 1.286 | 1.286 | 0.0000 | ❌ REJECT |
| 3 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_1_982376 | 1.286 | 1.892 | 3.0122 | ✅ ACCEPT |
| 4 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_2_301c87 | 1.286 | 2.113 | 3.7086 | ✅ ACCEPT |
| 5 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_3_af26dc | 1.286 | 1.892 | 3.0122 | ✅ ACCEPT |
| 6 | — |
gradient_boosting |
— | — | #7 | k_loop_iter_6_101a30 | 1.286 | 1.189 | -0.6505 | ❌ REJECT |
📄 Report Markdown
# AUTOLOOP: zz_sylvain (6 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**: 218.74s
> **Total accepted**: 4
> **Total rejected**: 2
## Iterations 詳情
### Iteration 1
- DSL: `k_high.pct_change(12) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high)` (feature=k_loop_iter_2_301c87)
- DSL valid: True
- FeatureSet candidate id: 916
- baseline PF: 1.286 → modified PF: 2.113
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 3.7086
- accepted: True, reason: accepted
**Metrics summary:**
- profit_factor: baseline=1.286, modified=2.113, diff=0.827
- sharpe_ratio: baseline=7.879, modified=21.700, diff=13.821
- win_rate: baseline=0.553, modified=0.596, diff=0.043
- max_drawdown: baseline=0.075, modified=0.051, diff=-0.023
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
### Iteration 2
- DSL: `k_high.pct_change(12) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high) * vol_ratio` (feature=k_loop_iter_3_4e9c71)
- DSL valid: True
- FeatureSet candidate id: 917
- 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)` (feature=k_loop_iter_1_982376)
- DSL valid: True
- FeatureSet candidate id: 918
- baseline PF: 1.286 → modified PF: 1.892
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 3.0122
- accepted: True, reason: accepted
**Metrics summary:**
- profit_factor: baseline=1.286, modified=1.892, diff=0.606
- sharpe_ratio: baseline=7.879, modified=19.176, diff=11.297
- win_rate: baseline=0.553, modified=0.600, diff=0.047
- max_drawdown: baseline=0.075, modified=0.054, diff=-0.021
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
### Iteration 4
- DSL: `k_high.pct_change(12) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high)` (feature=k_loop_iter_2_301c87)
- DSL valid: True
- FeatureSet candidate id: 919
- baseline PF: 1.286 → modified PF: 2.113
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 3.7086
- accepted: True, reason: accepted
**Metrics summary:**
- profit_factor: baseline=1.286, modified=2.113, diff=0.827
- sharpe_ratio: baseline=7.879, modified=21.700, diff=13.821
- win_rate: baseline=0.553, modified=0.596, diff=0.043
- max_drawdown: baseline=0.075, modified=0.051, diff=-0.023
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
### Iteration 5
- DSL: `k_high.pct_change(12) * i_rsi(k_close, 14) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high) / (1 + k_body_size_pct)` (feature=k_loop_iter_3_af26dc)
- DSL valid: True
- FeatureSet candidate id: 920
- baseline PF: 1.286 → modified PF: 1.892
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 3.0122
- accepted: True, reason: accepted
**Metrics summary:**
- profit_factor: baseline=1.286, modified=1.892, diff=0.606
- sharpe_ratio: baseline=7.879, modified=19.176, diff=11.297
- win_rate: baseline=0.553, modified=0.600, diff=0.047
- max_drawdown: baseline=0.075, modified=0.054, diff=-0.021
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
### Iteration 6
- DSL: `k_high.pct_change(12) * (k_high.pct_change(12) / (1 + atr_norm) * (1 - price_position) * (1 - dist_to_high))` (feature=k_loop_iter_6_101a30)
- DSL valid: True
- FeatureSet candidate id: 921
- baseline PF: 1.286 → modified PF: 1.189
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: -0.6505
- accepted: False, reason: p=1.000 ≥ 0.05, cohens_d=0.000 ≤ 0.3
**Metrics summary:**
- profit_factor: baseline=1.286, modified=1.189, diff=-0.097
- sharpe_ratio: baseline=7.879, modified=5.423, diff=-2.456
- win_rate: baseline=0.553, modified=0.532, diff=-0.021
- max_drawdown: baseline=0.075, modified=0.054, diff=-0.021
- test_accuracy: baseline=0.986, modified=0.986, diff=0.000
📊 Multi-Objective Metrics
Iteration 1: k_loop_iter_2_301c87
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: 3.7086
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.596 | 0.043 |
| max_drawdown | 0.075 | 0.051 | -0.023 |
| sharpe_ratio | 7.879 | 21.700 | 13.821 |
| profit_factor | 1.286 | 2.113 | 0.827 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
Iteration 2: k_loop_iter_3_4e9c71
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_1_982376
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: 3.0122
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.600 | 0.047 |
| max_drawdown | 0.075 | 0.054 | -0.021 |
| sharpe_ratio | 7.879 | 19.176 | 11.297 |
| profit_factor | 1.286 | 1.892 | 0.606 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
Iteration 4: k_loop_iter_2_301c87
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: 3.7086
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.596 | 0.043 |
| max_drawdown | 0.075 | 0.051 | -0.023 |
| sharpe_ratio | 7.879 | 21.700 | 13.821 |
| profit_factor | 1.286 | 2.113 | 0.827 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
Iteration 5: k_loop_iter_3_af26dc
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: 3.0122
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.600 | 0.047 |
| max_drawdown | 0.075 | 0.054 | -0.021 |
| sharpe_ratio | 7.879 | 19.176 | 11.297 |
| profit_factor | 1.286 | 1.892 | 0.606 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
Iteration 6: k_loop_iter_6_101a30
Y Label: — | Parent FS: #7
Objective mode: scalarize
Scalar score: -0.6505
| Metric | Baseline | Modified | Diff |
|---|---|---|---|
| win_rate | 0.553 | 0.532 | -0.021 |
| max_drawdown | 0.075 | 0.054 | -0.021 |
| sharpe_ratio | 7.879 | 5.423 | -2.456 |
| profit_factor | 1.286 | 1.189 | -0.097 |
| test_accuracy | 0.986 | 0.986 | 0.000 |
📁 Offline Report
Markdown backup: reports/autoloop/zz_sylvain/20260718_215954.md