跳到主要內容

Feature Iteration Run #1353: volume_price_pivot_v86_y_C0

Status: completed | Started: 2026-09-29 23:59:50 | Ended: 2026-09-29 23:59:57

📊 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 C0 gradient_boosting — — #2 ✅ 0.000 0.000 0.0000 0.000 1.000 0.000 ❌ REJECT propose v4.2: LLM 回應 parse_failed — reject 該輪（不靜默落 stub）。

📄 Report Markdown

# AUTOLOOP: volume_price_pivot_v86_y_C0 (1 iterations)

> **Phase**: Y4.7 Option B (DSL → Python code → FeatureSet candidate)
> **Target indicator**: volume_price_pivot_v86_y_C0
> **Base feature_set_id**: 2
> **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**: 7.05s
> **Total accepted**: 0
> **Total rejected**: 1

## 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）。

📊 Multi-Objective Metrics

Iteration 1:

Y Label: C0 | Parent FS: #2

Objective mode: single

Scalar score: 0.0000

📁 Offline Report

Markdown backup: reports/autoloop/volume_price_pivot_v86_y_C0/20260930_075957.md