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Feature Iteration Run #1873: zz_sylvain

Status: completed | Started: 2026-10-04 09:54:20 | Ended: 2026-10-04 09:55:39

📊 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_macd_hist_atr_norm macd_line = ta.ema(close, 12) - ta.ema(… ✅ 1.438 1.327 -0.5509 0.000 0.300 0.284 ❌ REJECT scalar_score -0.5509 <= 0.0, sharpe_delta -4.2802 (-34.41%) < -30%, hypothesis test not confirmed, DSR gate failed: champion SR=2.9016 ≤ expected_max=3.2608 (N=10 effective trials, PSR=0.4281), PBO gate failed: PBO=0.6037 > 0.5 (overfit likely)

📄 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**: 78.58s
> **Total accepted**: 0
> **Total rejected**: 1

## Iterations 詳情

### Iteration 1
- DSL: `macd_line = ta.ema(close, 12) - ta.ema(close, 26)
macd_signal = ta.ema(macd_line, 9)
macd_hist = macd_line - macd_signal
atr_v = ta.atr(high, low, close, 14)
result = macd_hist / (atr_v + 1e-8)` (feature=k_iter1_k_macd_hist_atr_norm)
- DSL valid: True
- FeatureSet candidate id: 1840
- baseline PF: 1.438 → modified PF: 1.327
- t_stat: 0.000, p_value: 0.300, cohens_d: 0.284
- scalar_score: -0.5509
- accepted: False, reason: scalar_score -0.5509 <= 0.0, sharpe_delta -4.2802 (-34.41%) < -30%, hypothesis test not confirmed, DSR gate failed: champion SR=2.9016 ≤ expected_max=3.2608 (N=10 effective trials, PSR=0.4281), PBO gate failed: PBO=0.6037 > 0.5 (overfit likely)

**Metrics summary:**
  - profit_factor: baseline=1.438, modified=1.327, diff=-0.112
  - sharpe_ratio: baseline=12.440, modified=8.160, diff=-4.280
  - win_rate: baseline=0.730, modified=0.504, diff=-0.225
  - max_drawdown: baseline=0.078, modified=0.144, diff=0.066
  - test_accuracy: baseline=0.983, modified=0.976, diff=-0.008

📊 Multi-Objective Metrics

Iteration 1: k_iter1_k_macd_hist_atr_norm

Y Label: C8 | Parent FS: #1748

Objective mode: scalarize

Scalar score: -0.5509

MetricBaselineModifiedDiff
win_rate 0.730 0.504 -0.225
max_drawdown 0.078 0.144 0.066
sharpe_ratio 12.440 8.160 -4.280
profit_factor 1.438 1.327 -0.112
test_accuracy 0.983 0.976 -0.008

📁 Offline Report

Markdown backup: reports/autoloop/zz_sylvain/20261004_175539.md