{
  "model_type": "LOBAlgoNet",
  "architecture": "BilinearNorm + Spatial CNN + Temporal CNN + Transformer Attention",
  "num_classes": 5,
  "class_names": [
    "TWAP",
    "VWAP",
    "ICEBERG",
    "SUPPORT",
    "NORMAL"
  ],
  "class_names_zh": [
    "TWAP(时间加权)",
    "VWAP(量加权)",
    "冰山订单",
    "护盘/支撑",
    "散户/正常"
  ],
  "seq_len": 100,
  "d_model": 128,
  "nhead": 4,
  "dropout": 0.25,
  "total_parameters": 338525,
  "test_accuracy": 0.5273182957393484,
  "test_f1_macro": 0.35382369182978163,
  "test_f1_weighted": 0.5822412019482407,
  "test_precision": [
    0.0,
    0.17391304347826086,
    0.9820359281437125,
    0.4684317718940937,
    0.23381294964028776
  ],
  "test_recall": [
    0.0,
    0.4444444444444444,
    0.5573491928632116,
    0.5764411027568922,
    0.3857566765578635
  ],
  "training_dataset": "LeonardoBerti/TRADES-LOB",
  "labeling_method": "Rule-based pseudo-labels from algorithm signature detection",
  "label_description": {
    "0_TWAP": "Time-Weighted Average Price execution (equal-size periodic orders)",
    "1_VWAP": "Volume-Weighted Average Price execution (volume-proportional orders)",
    "2_ICEBERG": "Iceberg/hidden orders (level-1 refill after fill, hidden volume)",
    "3_SUPPORT": "Support/resistance defense (persistent large orders at key levels)",
    "4_NORMAL": "Normal retail activity (no algorithmic signature detected)"
  },
  "normalization": "z-score (means/stds in norm_stats.npz)"
}