File size: 1,492 Bytes
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"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)"
} |