A15v3 Stack-LSTM W1-R²=0.9995 W2-R²=0.6855

nuaa_meta_v3.json

@@ -1,7 +1,7 @@
 {
   "version": "v3",
   "sprint": "A15",
-  "trained_at": "2026-04-01T20:37:04.609119+00:00",
+  "trained_at": "2026-04-01T21:09:19.819498+00:00",
   "paper": "Sayyad et al., Sensors 2023 doi:10.3390/s23125659",
   "architecture": "Stack-LSTM (3 layers, hidden=128)",
   "early_stop_patience": 3,
@@ -16,25 +16,25 @@
     "threshold_pct": 0.5,
     "n_selected": 19,
     "cols": [
+      "d_rms_Torsion_Z",
+      "d_std_Torsion_Z",
+      "a_rms_Spindle_Power",
+      "d_var_Torsion_Z",
+      "d_peak_amp_vib_x",
+      "a_mean_Bending_Moment_X",
       "a_mean_Axial_Force",
-      "a_mean_vib_x",
-      "a_peak_amp_Bending_Moment_Y",
       "a_rms_Axial_Force",
+      "a_p2p_Torsion_Z",
       "a_p2p_Bending_Moment_Y",
-      "d_rms_Bending_Moment_Y",
-      "d_var_Bending_Moment_Y",
-      "d_peak_amp_vib_y",
-      "d_p2p_vib_y",
-      "d_kurtosis_Bending_Moment_Y",
-      "d_std_Bending_Moment_Y",
-      "a_mean_vib_y",
       "a_skew_Torsion_Z",
-      "a_mean_Torsion_Z",
-      "d_p2p_Bending_Moment_Y",
-      "a_p2p_Torsion_Z",
-      "a_kurtosis_Bending_Moment_Y",
-      "d_p2p_vib_x",
-      "a_mean_Spindle_Power"
+      "a_rms_Bending_Moment_X",
+      "a_mean_vib_x",
+      "a_peak_amp_Torsion_Z",
+      "a_mean_vib_y",
+      "a_rms_Torsion_Z",
+      "a_mean_Spindle_Power",
+      "d_mean_vib_x",
+      "d_rms_Bending_Moment_Y"
     ]
   },
   "split": "70/30 temporal within each case",
@@ -52,23 +52,23 @@
     "Spindle_Current"
   ],
   "W1": {
-    "r2": -39.8721,
-    "rmse": 0.5453,
-    "mape": 1378.485,
-    "badge": "ESTIMATED",
+    "r2": 0.9995,
+    "rmse": 0.0067,
+    "mape": 6.472,
+    "badge": "VALIDATED",
     "paper_r2": 0.964,
     "paper_rmse": 0.051,
     "paper_mape": 3.676
   },
   "W2": {
-    "r2": -59.8982,
-    "rmse": 0.3475,
-    "mape": 1908.074,
+    "r2": 0.6855,
+    "rmse": 0.08,
+    "mape": 140.432,
     "paper_r2": 0.985,
     "paper_rmse": 0.034,
     "paper_mape": 2.728
   },
-  "total_ref_sec_w1": 3523.45,
+  "total_ref_sec_w1": 3505.35,
   "feat_mean_path": "feat_mean_v3.npy",
   "feat_std_path": "feat_std_v3.npy",
   "rf_cols_path": "rf_cols_v3.json"