Online Learning & Drift Detection
প্রতি ৩ ঘণ্টায় স্বয়ংক্রিয় model retrain · উন্নত হলেই deploy
কৌশল
Frequency
৩ ঘণ্টা
Auto retrain
Drift Threshold
১০%
CPU বা RAM mean
Deploy Policy
উন্নত হলে
Only improved
মোট Retrain
18
Online Learning এর প্রভাব — প্রমাণিত ফলাফল
CPU Forecast
আগে
৮.২০%
RMSE
→
পরে
২.৫৯%
RMSE
৬৮%
উন্নত
R²: ০.৫১১ → ০.৯৫১ · CPU Drift: ৮১.৮৩%
RAM Forecast
আগে
১.০৪%
RMSE
→
পরে
০.৫৯%
RMSE
৪৩%
উন্নত
R²: ০.৬৫২ → ০.৮৮৯ · RAM Drift: ০.৩৪%
RMSE উন্নতির গ্রাফ
Retrain ইতিহাস
| সময় | VPS | CPU আগে | CPU পরে | RAM আগে | RAM পরে | CPU Drift | Samples | Status |
|---|---|---|---|---|---|---|---|---|
| 2026-04-16 17:25:35 | V1003 | 6.2799% | 6.2429% ↓ | 1.0163% | 1.0200% ↑ | 24.1% | 2,746 | ✅ Deploy |
| 2026-04-16 14:25:15 | V1003 | 6.1186% | 6.0712% ↓ | 1.0102% | 1.0094% ↓ | 26.9% | 2,710 | ✅ Deploy |
| 2026-04-16 11:24:46 | V1003 | 6.2564% | 6.2289% ↓ | 0.9517% | 0.9555% ↑ | 20.9% | 2,673 | ✅ Deploy |
| 2026-04-16 08:24:33 | V1003 | 5.9309% | 5.9350% ↑ | 0.9334% | 0.9368% ↑ | 17.3% | 2,637 | Skip |
| 2026-04-16 05:24:14 | V1003 | 5.5655% | 5.6644% ↑ | 0.9411% | 0.9487% ↑ | 19.1% | 2,601 | Skip |
| 2026-04-16 02:24:01 | V1003 | 5.3220% | 5.4896% ↑ | 0.9502% | 0.9557% ↑ | 31.9% | 2,565 | Skip |
| 2026-04-15 23:23:56 | V1003 | 5.1647% | 5.6499% ↑ | 0.9404% | 0.9336% ↓ | 21.7% | 2,529 | ✅ Deploy |
| 2026-04-15 20:23:45 | V1003 | 4.7793% | 5.4595% ↑ | 0.9284% | 0.9690% ↑ | 42.3% | 2,493 | Skip |
| 2026-04-15 17:23:34 | V1003 | 4.5281% | 5.4035% ↑ | 0.8922% | 0.9497% ↑ | 52.3% | 2,457 | Skip |
| 2026-04-15 14:23:30 | V1003 | 4.3167% | 5.4168% ↑ | 0.8226% | 0.9118% ↑ | 47.9% | 2,421 | Skip |
| 2026-04-15 11:23:27 | V1003 | 4.1888% | 5.8651% ↑ | 0.7780% | 0.8882% ↑ | 36.2% | 2,385 | Skip |
| 2026-04-15 08:23:24 | V1003 | 4.0203% | 6.1929% ↑ | 0.7525% | 0.8881% ↑ | 50.3% | 2,349 | Skip |
| 2026-04-15 05:23:20 | V1003 | 3.9943% | 6.5205% ↑ | 0.7336% | 0.8867% ↑ | 42.0% | 2,313 | Skip |
| 2026-04-15 02:23:18 | V1003 | 3.9300% | 7.0246% ↑ | 0.7248% | 0.9485% ↑ | 43.1% | 2,277 | Skip |
| 2026-04-14 23:23:14 | V1003 | 3.7970% | 7.2988% ↑ | 0.6865% | 0.9806% ↑ | 46.5% | 2,241 | Skip |
| 2026-04-14 23:15:04 | V1003 | 3.7959% | 7.4096% ↑ | 0.6866% | 0.9940% ↑ | 47.9% | 2,239 | Skip |
| 2026-04-14 21:40:50 | V1003 | 3.7797% | 7.5459% ↑ | 0.6751% | 1.0009% ↑ | 53.0% | 2,221 | Skip |
| 2026-04-14 20:38:15 | V1003 | 3.8029% | 7.6051% ↑ | 0.6783% | 1.0128% ↑ | 57.7% | 2,208 | Skip |
কীভাবে কাজ করে
📊
সংগ্রহ
প্রতি ৩০ সেকেন্ডে নতুন data
📈
Drift শনাক্ত
নতুন vs পুরনো mean তুলনা
🔄
Retrain
XGBoost পুনরায় train
✅
যাচাই
পুরনো vs নতুন RMSE
🚀
Deploy
উন্নত হলেই replace