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metrics.json

@@ -3,8 +3,8 @@
     "split": "xgb_val",
     "n_samples": 422,
     "n_races": 22,
-    "log_loss": 0.04428521632127945,
-    "brier_score": 0.012726294808089733,
+    "log_loss": 0.050907751783122394,
+    "brier_score": 0.015055796131491661,
     "top1_accuracy": 0.8636363636363636,
     "top3_accuracy": 1.0,
     "top5_accuracy": 1.0
@@ -13,30 +13,10 @@
     "split": "xgb_test",
     "n_samples": 927,
     "n_races": 47,
-    "log_loss": 0.1335874041303076,
-    "brier_score": 0.0421573743224144,
-    "top1_accuracy": 0.40425531914893614,
-    "top3_accuracy": 0.8936170212765957,
-    "top5_accuracy": 1.0
-  },
-  {
-    "split": "lgbm_val",
-    "n_samples": 422,
-    "n_races": 22,
-    "log_loss": 0.055231699866363795,
-    "brier_score": 0.016524415564765985,
-    "top1_accuracy": 0.8181818181818182,
-    "top3_accuracy": 0.9545454545454546,
-    "top5_accuracy": 1.0
-  },
-  {
-    "split": "lgbm_test",
-    "n_samples": 927,
-    "n_races": 47,
-    "log_loss": 0.14978252709187923,
-    "brier_score": 0.043730167655318064,
-    "top1_accuracy": 0.44680851063829785,
-    "top3_accuracy": 0.851063829787234,
-    "top5_accuracy": 1.0
+    "log_loss": 0.13834304642624395,
+    "brier_score": 0.04351075738668442,
+    "top1_accuracy": 0.5106382978723404,
+    "top3_accuracy": 0.9148936170212766,
+    "top5_accuracy": 0.9787234042553191
   }
 ]