Update draws, retrain models and generate tips for May 22+26 draws

- Added missing 2026-05-22 and 2026-05-26 draws to AlleEurojackpotzahlen.csv
- Retroactive learning applied for both new draws (42 total cycles)
- Retrained RF and LSTM models on 955 draws
- Generated fresh tips: weekly_tips_20260528_091341.csv

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

data/AlleEurojackpotzahlen.csv

@@ -951,3 +951,6 @@ datum;Z1;Z2;Z3;Z4;Z5;SZ1;SZ2
 2026-05-08;3;17;18;31;41;6;12
 2026-05-12;7;15;19;28;35;3;11
 2026-05-15;1;32;33;36;37;7;12
+2026-05-19;10;36;37;39;47;5;6
+2026-05-22;5;34;35;42;46;3;5
+2026-05-26;5;11;23;33;42;10;12

data/eurojackpot_ml_models/deep_learning_euro/lstm_config_12.json

@@ -1,9 +1,9 @@
 {
-  "trained_at": "2026-05-19T09:04:48.801117",
+  "trained_at": "2026-05-28T09:13:40.676218",
-  "num_samples": 932,
+  "num_samples": 935,
   "num_features": 20,
-  "final_loss": 0.33304641644159955,
+  "final_loss": 0.3379375835259755,
-  "final_val_loss": 0.32588819166024524,
+  "final_val_loss": 0.32764050861199695,
-  "best_val_loss": 0.32180650532245636,
+  "best_val_loss": 0.32431263228257495,
-  "epochs_trained": 26
+  "epochs_trained": 22
 }

data/eurojackpot_ml_models/deep_learning_main/lstm_config_50.json

@@ -1,9 +1,9 @@
 {
-  "trained_at": "2026-05-19T09:04:39.307548",
+  "trained_at": "2026-05-28T09:13:33.008205",
-  "num_samples": 932,
+  "num_samples": 935,
   "num_features": 20,
-  "final_loss": 0.3328763085107009,
+  "final_loss": 0.3324982014795144,
-  "final_val_loss": 0.32958758374055225,
+  "final_val_loss": 0.32942695915699005,
-  "best_val_loss": 0.32844950755437213,
+  "best_val_loss": 0.32826374967892963,
-  "epochs_trained": 22
+  "epochs_trained": 21
 }

data/eurojackpot_ml_models/learning_state.json

@@ -1,78 +1,78 @@
 {
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   "stats": {
-    "incorrect_main": 1710,
+    "incorrect_main": 1890,
-    "correct_main": 190,
+    "correct_main": 210,
-    "incorrect_euro": 380,
+    "incorrect_euro": 420,
-    "correct_euro": 76,
+    "correct_euro": 84,
-    "cycles": 38,
+    "cycles": 42,
-    "last_update": "2026-05-19T09:04:48.805027"
+    "last_update": "2026-05-28T09:12:56.352841"
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   "learning_rate": 0.1,
-  "last_saved": "2026-05-19T09:04:48.805048"
+  "last_saved": "2026-05-28T09:12:56.352882"
 }

data/generated_tips/generation_history.json

@@ -405,6 +405,20 @@
       "file": "weekly_tips_20260519_093017.csv",
       "avg_confidence": 0.47597948672799795,
       "avg_quality": 0.5941141824821975
+    },
+    {
+      "timestamp": "2026-05-19T13:45:39.737333",
+      "num_tips": 10,
+      "file": "weekly_tips_20260519_134539.csv",
+      "avg_confidence": 0.49394431934763094,
+      "avg_quality": 0.605360768481602
+    },
+    {
+      "timestamp": "2026-05-28T09:13:41.489560",
+      "num_tips": 10,
+      "file": "weekly_tips_20260528_091341.csv",
+      "avg_confidence": 0.5085910996509726,
+      "avg_quality": 0.6122512647691146
     }
   ]
 }

data/learning_log.json

@@ -518,6 +518,59 @@
         "euro": 0.0
       },
       "note": "retroactive_learning"
+    },
+    {
+      "timestamp": "2026-05-19T13:37:27.815058",
+      "draw_date": "2026-05-15",
+      "evaluation": {
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+        "euro": 1,
+        "tip": 8
+      },
+      "avg_matches": {
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+        "euro": 0.3
+      }
+    },
+    {
+      "timestamp": "2026-05-20T08:00:41.414855",
+      "draw_date": "2026-05-19",
+      "evaluation": {
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+        "tip": 6
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+    },
+    {
+      "timestamp": "2026-05-28T09:10:00.000000",
+      "draw_date": "2026-05-22",
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+      "note": "retroactive_learning"
+    },
+    {
+      "timestamp": "2026-05-28T09:05:24.444697",
+      "draw_date": "2026-05-26",
+      "evaluation": {
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+        "euro": 0,
+        "tip": 1
+      },
+      "avg_matches": {
+        "main": 1.2,
+        "euro": 0.0
+      }
     }
   ]
 }