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 17:25:37 | V1011 | 10.9212% | 10.9212% ↑ | 1.1186% | 1.1186% ↑ | 9.9% | 2,746 | Skip |
| 2026-04-16 14:25:23 | V1011 | 10.9490% | 10.9212% ↓ | 1.1204% | 1.1186% ↓ | 11.4% | 2,710 | ✅ Deploy |
| 2026-04-16 11:24:54 | V1011 | 10.7969% | 10.7791% ↓ | 1.0972% | 1.1137% ↑ | 21.6% | 2,673 | ✅ Deploy |
| 2026-04-16 08:24:34 | V1011 | 10.8450% | 10.7792% ↓ | 1.1366% | 1.1268% ↓ | 34.0% | 2,637 | ✅ Deploy |
| 2026-04-16 05:24:15 | V1011 | 10.7487% | 10.7742% ↑ | 1.0448% | 1.0647% ↑ | 47.3% | 2,601 | Skip |
| 2026-04-16 02:24:02 | V1011 | 10.7126% | 10.8086% ↑ | 1.0081% | 1.0179% ↑ | 10.2% | 2,565 | Skip |
| 2026-04-15 23:23:58 | V1011 | 10.1252% | 10.1252% ↑ | 0.9977% | 0.9977% ↑ | 5.3% | 2,529 | Skip |
| 2026-04-15 20:23:46 | V1011 | 10.1252% | 10.6533% ↑ | 0.9977% | 1.0444% ↑ | 25.4% | 2,493 | Skip |
| 2026-04-15 17:23:34 | V1011 | 9.3895% | 9.3895% ↑ | 0.9890% | 0.9890% ↑ | 9.9% | 2,457 | Skip |
| 2026-04-15 14:23:30 | V1011 | 9.3895% | 10.1705% ↑ | 0.9890% | 1.1037% ↑ | 27.0% | 2,421 | Skip |
| 2026-04-15 11:23:27 | V1011 | 8.9134% | 9.8771% ↑ | 0.8942% | 1.0098% ↑ | 11.5% | 2,385 | Skip |
| 2026-04-15 08:23:24 | V1011 | 7.9000% | 7.9000% ↑ | 0.8005% | 0.8005% ↑ | 6.1% | 2,349 | Skip |
| 2026-04-15 05:23:21 | V1011 | 7.9000% | 9.1244% ↑ | 0.8005% | 0.9303% ↑ | 41.6% | 2,313 | Skip |
| 2026-04-15 02:23:18 | V1011 | 7.6006% | 9.2680% ↑ | 0.7713% | 0.9210% ↑ | 34.8% | 2,277 | Skip |
| 2026-04-14 23:23:15 | V1011 | 7.1952% | 9.1616% ↑ | 0.7138% | 0.8933% ↑ | 52.2% | 2,241 | Skip |
| 2026-04-14 23:15:05 | V1011 | 7.1958% | 9.1735% ↑ | 0.7138% | 0.8900% ↑ | 53.0% | 2,240 | Skip |
| 2026-04-14 21:40:51 | V1011 | 7.1297% | 9.2638% ↑ | 0.7375% | 0.9431% ↑ | 44.9% | 2,221 | Skip |
| 2026-04-14 20:38:15 | V1011 | 7.0827% | 9.3475% ↑ | 0.7350% | 0.9551% ↑ | 45.7% | 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