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 17:25:25 | V1001 | 5.1907% | 5.3652% ↑ | 1.4930% | 1.7251% ↑ | 21.4% | 2,746 | Skip |
| 2026-04-16 14:24:57 | V1001 | 5.1938% | 5.3506% ↑ | 1.4909% | 1.4529% ↓ | 22.9% | 2,709 | ✅ Deploy |
| 2026-04-16 11:24:37 | V1001 | 5.1644% | 5.1944% ↑ | 1.4954% | 1.7475% ↑ | 21.9% | 2,673 | Skip |
| 2026-04-16 08:24:16 | V1001 | 5.1884% | 5.2340% ↑ | 1.5397% | 1.4872% ↓ | 25.0% | 2,637 | ✅ Deploy |
| 2026-04-16 05:24:03 | V1001 | 5.1517% | 5.1529% ↑ | 1.5154% | 1.6811% ↑ | 13.1% | 2,601 | Skip |
| 2026-04-16 02:23:59 | V1001 | 5.0650% | 5.0928% ↑ | 1.4791% | 1.7081% ↑ | 1.0% | 2,565 | Skip |
| 2026-04-15 23:23:46 | V1001 | 5.1035% | 5.0043% ↓ | 1.3918% | 1.6033% ↑ | 11.4% | 2,529 | ✅ Deploy |
| 2026-04-15 20:23:35 | V1001 | 4.9209% | 4.9319% ↑ | 1.3732% | 1.7545% ↑ | 2.3% | 2,493 | Skip |
| 2026-04-15 17:23:31 | V1001 | 4.5102% | 4.5102% ↑ | 1.2083% | 1.2083% ↑ | 2.6% | 2,457 | Skip |
| 2026-04-15 14:23:28 | V1001 | 4.5102% | 4.7181% ↑ | 1.2083% | 1.8723% ↑ | 7.9% | 2,421 | Skip |
| 2026-04-15 11:23:25 | V1001 | 4.2803% | 4.5501% ↑ | 1.1745% | 1.5589% ↑ | 0.8% | 2,385 | Skip |
| 2026-04-15 08:23:22 | V1001 | 4.1388% | 4.5696% ↑ | 1.1271% | 1.6988% ↑ | 8.2% | 2,349 | Skip |
| 2026-04-15 05:23:19 | V1001 | 3.7887% | 3.7887% ↑ | 0.9628% | 0.9628% ↑ | 0.9% | 2,313 | Skip |
| 2026-04-15 02:23:16 | V1001 | 3.7887% | 4.5027% ↑ | 0.9628% | 1.5198% ↑ | 9.8% | 2,277 | Skip |
| 2026-04-14 23:23:13 | V1001 | 3.5491% | 4.3451% ↑ | 0.9299% | 1.4784% ↑ | 0.7% | 2,241 | Skip |
| 2026-04-14 23:15:02 | V1001 | 3.5436% | 4.2925% ↑ | 0.9298% | 1.4721% ↑ | 1.6% | 2,239 | Skip |
| 2026-04-14 21:40:48 | V1001 | 3.4309% | 4.3338% ↑ | 0.9103% | 1.6594% ↑ | 2.1% | 2,221 | Skip |
| 2026-04-14 20:38:13 | V1001 | 3.3782% | 4.3898% ↑ | 0.8674% | 1.8021% ↑ | 8.8% | 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