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Feature Iteration Run #835: zz_sylvain

Status: completed | Started: 2026-07-21 07:52:05 | Ended: 2026-07-21 07:56:29

⭐ Best Accepted Iteration

Iteration 8: k_high.pct_change(12) * (1 + hl_range) * (1 - dist_to_high)…

baseline PF: 1.947 → modified PF: 2.610 | Cohen's d: 0.618 | p-value: 0.000

📊 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 — gradient_boosting — — #7 k_loop_iter_6_301c87 k_high.pct_change(12) / (1 + atr_norm) … ✅ 1.947 2.466 0.6193 0.000 0.296 0.211 ✅ ACCEPT accepted
2 — gradient_boosting — — #7 k_loop_iter_2_1a1aba k_high.pct_change(12) * (1 + hl_range) … ✅ 1.947 2.466 1.3886 0.000 0.012 0.388 ✅ ACCEPT accepted
3 — gradient_boosting — — #7 k_loop_iter_3_3b108c k_momentum_pct_change / (1 + o_div_ampl… ✅ 1.947 0.775 -3.3916 0.000 0.278 0.577 ❌ REJECT min_p=0.278 ≥ 0.05, constraints: ['sharpe_ratio >= 1.0: got -7.5544']
4 — gradient_boosting — — #7 k_loop_iter_4_5819f2 k_high.pct_change(12) * (1 + hl_range) … ✅ 1.947 2.466 1.3886 0.000 0.012 0.388 ✅ ACCEPT accepted
5 — gradient_boosting — — #7 k_loop_iter_5_2727df k_high.pct_change(12) * (1 + hl_range) … ✅ 1.947 2.466 1.3886 0.000 0.012 0.388 ✅ ACCEPT accepted
6 — gradient_boosting — — #7 k_iter6_k_momentum_pct_chang_hl_range_i_rsi_k_close k_momentum_pct_change / (1 + o_div_ampl… ❌ 0.000 0.000 0.0000 0.000 1.000 0.000 ❌ REJECT safe_eval DSL: 變數未定義: o_div_amplitude
7 — gradient_boosting — — #7 k_loop_iter_7_ea31d7 k_high.pct_change(12) * (1 + hl_range) … ✅ 1.947 2.401 0.9424 0.000 0.021 0.388 ✅ ACCEPT accepted
8 — gradient_boosting — — #7 k_loop_iter_8_94dd57 k_high.pct_change(12) * (1 + hl_range) … ✅ 1.947 2.610 2.1204 0.000 0.000 0.618 ✅ ACCEPT accepted

📄 Report Markdown

# AUTOLOOP: zz_sylvain (8 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**: 263.45s
> **Total accepted**: 6
> **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_6_301c87)
- DSL valid: True
- FeatureSet candidate id: 1159
- baseline PF: 1.947 → modified PF: 2.466
- t_stat: 0.000, p_value: 0.296, cohens_d: 0.211
- scalar_score: 0.6193
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.466, diff=0.519
  - sharpe_ratio: baseline=19.162, modified=24.727, diff=5.565
  - win_rate: baseline=0.600, modified=0.636, diff=0.036
  - max_drawdown: baseline=0.056, modified=0.050, diff=-0.006
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 2
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - price_position) * (1 - dist_to_low)` (feature=k_loop_iter_2_1a1aba)
- DSL valid: True
- FeatureSet candidate id: 1160
- baseline PF: 1.947 → modified PF: 2.466
- t_stat: 0.000, p_value: 0.012, cohens_d: 0.388
- scalar_score: 1.3886
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.466, diff=0.519
  - sharpe_ratio: baseline=19.162, modified=24.727, diff=5.565
  - win_rate: baseline=0.600, modified=0.636, diff=0.036
  - max_drawdown: baseline=0.056, modified=0.050, diff=-0.006
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 3
- DSL: `k_momentum_pct_change / (1 + o_div_amplitude_12) * (1 + hl_range)` (feature=k_loop_iter_3_3b108c)
- DSL valid: True
- FeatureSet candidate id: 1161
- baseline PF: 1.947 → modified PF: 0.775
- t_stat: 0.000, p_value: 0.278, cohens_d: 0.577
- scalar_score: -3.3916
- accepted: False, reason: min_p=0.278 ≥ 0.05, constraints: ['sharpe_ratio >= 1.0: got -7.5544']

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=0.775, diff=-1.172
  - sharpe_ratio: baseline=19.162, modified=-7.554, diff=-26.717
  - win_rate: baseline=0.600, modified=0.424, diff=-0.176
  - max_drawdown: baseline=0.056, modified=0.131, diff=0.075
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.001

### Iteration 4
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - dist_to_high) * (1 - price_position) * (1 - dist_to_low)` (feature=k_loop_iter_4_5819f2)
- DSL valid: True
- FeatureSet candidate id: 1162
- baseline PF: 1.947 → modified PF: 2.466
- t_stat: 0.000, p_value: 0.012, cohens_d: 0.388
- scalar_score: 1.3886
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.466, diff=0.519
  - sharpe_ratio: baseline=19.162, modified=24.727, diff=5.565
  - win_rate: baseline=0.600, modified=0.636, diff=0.036
  - max_drawdown: baseline=0.056, modified=0.050, diff=-0.006
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 5
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - dist_to_high) * (1 + return_5)` (feature=k_loop_iter_5_2727df)
- DSL valid: True
- FeatureSet candidate id: 1163
- baseline PF: 1.947 → modified PF: 2.466
- t_stat: 0.000, p_value: 0.012, cohens_d: 0.388
- scalar_score: 1.3886
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.466, diff=0.519
  - sharpe_ratio: baseline=19.162, modified=24.727, diff=5.565
  - win_rate: baseline=0.600, modified=0.636, diff=0.036
  - max_drawdown: baseline=0.056, modified=0.050, diff=-0.006
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.000

### Iteration 6
- DSL: `k_momentum_pct_change / (1 + o_div_amplitude(12)) * (1 + hl_range) * i_rsi(k_close, 14) / 100` (feature=k_iter6_k_momentum_pct_chang_hl_range_i_rsi_k_close)
- DSL valid: False
- 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: safe_eval DSL: 變數未定義: o_div_amplitude

### Iteration 7
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - dist_to_high) * (1 - price_position) * i_rsi(k_close, 14) / 100` (feature=k_loop_iter_7_ea31d7)
- DSL valid: True
- FeatureSet candidate id: 1164
- baseline PF: 1.947 → modified PF: 2.401
- t_stat: 0.000, p_value: 0.021, cohens_d: 0.388
- scalar_score: 0.9424
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.401, diff=0.453
  - sharpe_ratio: baseline=19.162, modified=23.405, diff=4.243
  - win_rate: baseline=0.600, modified=0.548, diff=-0.052
  - max_drawdown: baseline=0.056, modified=0.056, diff=0.000
  - test_accuracy: baseline=0.992, modified=0.992, diff=-0.001

### Iteration 8
- DSL: `k_high.pct_change(12) * (1 + hl_range) * (1 - dist_to_high) * i_macd(k_close, 12, 26, 9) / (1 + atr_norm)` (feature=k_loop_iter_8_94dd57)
- DSL valid: True
- FeatureSet candidate id: 1165
- baseline PF: 1.947 → modified PF: 2.610
- t_stat: 0.000, p_value: 0.000, cohens_d: 0.618
- scalar_score: 2.1204
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.947, modified=2.610, diff=0.663
  - sharpe_ratio: baseline=19.162, modified=26.819, diff=7.657
  - win_rate: baseline=0.600, modified=0.667, diff=0.067
  - max_drawdown: baseline=0.056, modified=0.042, diff=-0.014
  - test_accuracy: baseline=0.992, modified=0.993, diff=0.000

📊 Multi-Objective Metrics

Iteration 1: k_loop_iter_6_301c87

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: 0.6193

MetricBaselineModifiedDiff
win_rate 0.600 0.636 0.036
max_drawdown 0.056 0.050 -0.006
sharpe_ratio 19.162 24.727 5.565
profit_factor 1.947 2.466 0.519
test_accuracy 0.992 0.992 0.000

Iteration 2: k_loop_iter_2_1a1aba

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: 1.3886

MetricBaselineModifiedDiff
win_rate 0.600 0.636 0.036
max_drawdown 0.056 0.050 -0.006
sharpe_ratio 19.162 24.727 5.565
profit_factor 1.947 2.466 0.519
test_accuracy 0.992 0.992 0.000

Iteration 3: k_loop_iter_3_3b108c

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: -3.3916

Failed constraints: sharpe_ratio >= 1.0: got -7.5544

MetricBaselineModifiedDiff
win_rate 0.600 0.424 -0.176
max_drawdown 0.056 0.131 0.075
sharpe_ratio 19.162 -7.554 -26.717
profit_factor 1.947 0.775 -1.172
test_accuracy 0.992 0.992 -0.001

Iteration 4: k_loop_iter_4_5819f2

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: 1.3886

MetricBaselineModifiedDiff
win_rate 0.600 0.636 0.036
max_drawdown 0.056 0.050 -0.006
sharpe_ratio 19.162 24.727 5.565
profit_factor 1.947 2.466 0.519
test_accuracy 0.992 0.992 0.000

Iteration 5: k_loop_iter_5_2727df

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: 1.3886

MetricBaselineModifiedDiff
win_rate 0.600 0.636 0.036
max_drawdown 0.056 0.050 -0.006
sharpe_ratio 19.162 24.727 5.565
profit_factor 1.947 2.466 0.519
test_accuracy 0.992 0.992 0.000

Iteration 6: k_iter6_k_momentum_pct_chang_hl_range_i_rsi_k_close

Y Label: — | Parent FS: #7

Objective mode: single

Scalar score: 0.0000

Iteration 7: k_loop_iter_7_ea31d7

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: 0.9424

MetricBaselineModifiedDiff
win_rate 0.600 0.548 -0.052
max_drawdown 0.056 0.056 0.000
sharpe_ratio 19.162 23.405 4.243
profit_factor 1.947 2.401 0.453
test_accuracy 0.992 0.992 -0.001

Iteration 8: k_loop_iter_8_94dd57

Y Label: — | Parent FS: #7

Objective mode: scalarize

Scalar score: 2.1204

MetricBaselineModifiedDiff
win_rate 0.600 0.667 0.067
max_drawdown 0.056 0.042 -0.014
sharpe_ratio 19.162 26.819 7.657
profit_factor 1.947 2.610 0.663
test_accuracy 0.992 0.993 0.000

📁 Offline Report

Markdown backup: reports/autoloop/zz_sylvain/20260721_155629.md