SniperGold_ML/ml/p3/baseline/output/p3_s18_baseline_results.json

{
  "generated_utc": "2026-08-24T00:00:11.561916+00:00",
  "models": [
    "logistic",
    "tree_depth3",
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    "mlp16"
  ],
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        "n": 115,
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    },
    "mlp16": {
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        "win_precision": 0.15,
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        "n": 113,
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        "n_loss": 83
      },
      "test": {
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        "brier": 0.3073426618221339,
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        "win_precision": 0.390625,
        "win_recall": 0.7352941176470589,
        "n": 115,
        "n_win": 34,
        "n_loss": 81
      }
    }
  },
  "test_confusion": [
    {
      "model": "logistic",
      "test_WIN_predWIN": 3,
      "test_WIN_predLOSS": 31,
      "test_LOSS_predWIN": 7,
      "test_LOSS_predLOSS": 74
    },
    {
      "model": "tree_depth3",
      "test_WIN_predWIN": 3,
      "test_WIN_predLOSS": 31,
      "test_LOSS_predWIN": 9,
      "test_LOSS_predLOSS": 72
    },
    {
      "model": "boost_small",
      "test_WIN_predWIN": 3,
      "test_WIN_predLOSS": 31,
      "test_LOSS_predWIN": 6,
      "test_LOSS_predLOSS": 75
    },
    {
      "model": "mlp16",
      "test_WIN_predWIN": 25,
      "test_WIN_predLOSS": 9,
      "test_LOSS_predWIN": 39,
      "test_LOSS_predLOSS": 42
    }
  ],
  "unresolved_ambiguous_counts": {
    "all_unresolved": 22,
    "all_ambiguous": 5,
    "lead_unresolved": 18,
    "lead_ambiguous": 5,
    "note": "UNRESOLVED/AMBIGUOUS retained in the dataset, excluded from the binary fit, reported here (never destroyed)."
  },
  "feature_sha16": "0414e401522ea4e2"
}