Online Learning & Drift Detection
প্রতি ৩ ঘণ্টায় স্বয়ংক্রিয় model retrain · উন্নত হলেই deploy
Retraining Strategy
Frequency
৩ ঘণ্টা
Auto scheduled
Drift Threshold
১০%
CPU বা RAM mean drift
Deploy Policy
উন্নত হলে
Only if RMSE improves
মোট Retrain
50
এখন পর্যন্ত
🚀 সফল Deploy
16
মোট 50 retrain এর মধ্যে
📉 সর্বশেষ CPU RMSE
8.02%
আগে ছিল: 7.93%
⚡ সর্বশেষ CPU Drift
28.5%
Threshold: 10% · V1011
সর্বশেষ Retrain এর প্রভাব — Real-time Database থেকে
🧠 CPU Forecast — V1011 · 2026-08-13 09:47
আগে
7.93%
RMSE
→
পরে
8.02%
RMSE
1% ↑
খারাপ
Drift: 28.5%
· R²: 0.907 → 0.905
· Samples: 29,272
💾 RAM Forecast — V1011 · 2026-08-13 09:47
আগে
3.70%
RMSE
→
পরে
3.74%
RMSE
1% ↑
খারাপ
RAM Drift: 37.4%
· Deploy: ⏭️ Skip
RMSE উন্নতির গ্রাফ
CPU RMSE (%)
RAM RMSE (%)
Retrain ইতিহাস (সর্বশেষ 50টি)
| সময় | VPS | CPU আগে | CPU পরে | RAM আগে | RAM পরে | CPU Drift | Samples | Status |
|---|---|---|---|---|---|---|---|---|
| 2026-08-13 09:47 | V1011 | 7.9251% | 8.0197% ↑ | 3.7044% | 3.7435% ↑ | 28.5% | 29,272 | ⏭️ Skip |
| 2026-08-13 09:47 | V1001 | 5.6780% | 5.6788% ↑ | 3.0205% | 2.9948% ↓ | 31.5% | 28,752 | ✅ Deploy |
| 2026-08-13 09:47 | V1003 | 2.9009% | 3.1203% ↑ | 0.7672% | 0.7711% ↑ | 65.5% | 29,272 | ⏭️ Skip |
| 2026-08-13 09:47 | V1009 | 3.9841% | 4.0208% ↑ | 0.6120% | 0.6398% ↑ | 66.6% | 29,134 | ⏭️ Skip |
| 2026-08-13 06:46 | V1011 | 7.9573% | 8.0358% ↑ | 3.6659% | 3.7113% ↑ | 87.6% | 29,236 | ⏭️ Skip |
| 2026-08-13 06:46 | V1001 | 5.6679% | 5.6676% ↓ | 3.0417% | 3.0660% ↑ | 13.8% | 28,716 | ✅ Deploy |
| 2026-08-13 06:46 | V1003 | 2.9282% | 3.0373% ↑ | 0.7687% | 0.7723% ↑ | 69.6% | 29,236 | ⏭️ Skip |
| 2026-08-13 06:46 | V1009 | 3.9832% | 4.0538% ↑ | 0.6067% | 0.6292% ↑ | 66.6% | 29,098 | ⏭️ Skip |
| 2026-08-13 03:46 | V1011 | 7.9743% | 8.1042% ↑ | 3.6561% | 3.7109% ↑ | 50.0% | 29,200 | ⏭️ Skip |
| 2026-08-13 03:46 | V1001 | 5.6750% | 5.6719% ↓ | 3.0480% | 3.0394% ↓ | 28.7% | 28,680 | ✅ Deploy |
| 2026-08-13 03:46 | V1003 | 2.9244% | 3.0569% ↑ | 0.7681% | 0.7726% ↑ | 61.9% | 29,200 | ⏭️ Skip |
| 2026-08-13 03:46 | V1009 | 4.0139% | 4.0764% ↑ | 0.6061% | 0.6365% ↑ | 63.0% | 29,062 | ⏭️ Skip |
| 2026-08-13 00:46 | V1011 | 7.9744% | 8.0717% ↑ | 3.6584% | 3.7050% ↑ | 21.8% | 29,164 | ⏭️ Skip |
| 2026-08-13 00:45 | V1001 | 5.6810% | 5.6857% ↑ | 3.0815% | 3.0551% ↓ | 19.1% | 28,644 | ✅ Deploy |
| 2026-08-13 00:45 | V1003 | 2.9191% | 2.9756% ↑ | 0.7677% | 0.7713% ↑ | 61.8% | 29,164 | ⏭️ Skip |
| 2026-08-13 00:45 | V1009 | 4.0355% | 4.1413% ↑ | 0.6086% | 0.6205% ↑ | 55.1% | 29,026 | ⏭️ Skip |
| 2026-08-12 21:45 | V1011 | 7.9971% | 8.1023% ↑ | 3.6608% | 3.6925% ↑ | 22.6% | 29,127 | ⏭️ Skip |
| 2026-08-12 21:45 | V1001 | 5.6734% | 5.6767% ↑ | 3.0902% | 3.0760% ↓ | 25.3% | 28,607 | ✅ Deploy |
| 2026-08-12 21:45 | V1003 | 2.9182% | 3.0006% ↑ | 0.7684% | 0.7715% ↑ | 64.1% | 29,127 | ⏭️ Skip |
| 2026-08-12 21:45 | V1009 | 4.0354% | 4.1119% ↑ | 0.6087% | 0.6296% ↑ | 60.2% | 28,989 | ⏭️ Skip |
| 2026-08-12 18:45 | V1011 | 8.0134% | 8.0984% ↑ | 3.6631% | 3.6811% ↑ | 5.7% | 29,091 | ⏭️ Skip |
| 2026-08-12 18:44 | V1001 | 5.6866% | 5.6792% ↓ | 3.1044% | 3.1116% ↑ | 31.5% | 28,571 | ✅ Deploy |
| 2026-08-12 18:44 | V1003 | 2.9217% | 3.0526% ↑ | 0.7678% | 0.7708% ↑ | 54.5% | 29,091 | ⏭️ Skip |
| 2026-08-12 18:44 | V1009 | 4.0367% | 4.0780% ↑ | 0.6070% | 0.6283% ↑ | 55.6% | 28,953 | ⏭️ Skip |
| 2026-08-12 15:44 | V1011 | 8.0108% | 8.1107% ↑ | 3.6704% | 3.7282% ↑ | 10.2% | 29,055 | ⏭️ Skip |
| 2026-08-12 15:44 | V1001 | 5.7017% | 5.7060% ↑ | 3.2793% | 3.1114% ↓ | 7.3% | 28,535 | ✅ Deploy |
| 2026-08-12 15:44 | V1003 | 2.9119% | 3.1262% ↑ | 0.7700% | 0.7720% ↑ | 50.7% | 29,055 | ⏭️ Skip |
| 2026-08-12 15:44 | V1009 | 4.0505% | 4.0861% ↑ | 0.6074% | 0.6330% ↑ | 51.6% | 28,917 | ⏭️ Skip |
| 2026-08-12 12:44 | V1011 | 8.0066% | 8.1698% ↑ | 3.6622% | 3.6980% ↑ | 13.0% | 29,019 | ⏭️ Skip |
| 2026-08-12 12:43 | V1001 | 5.7004% | 5.6956% ↓ | 3.3944% | 3.4004% ↑ | 15.8% | 28,499 | ✅ Deploy |
| 2026-08-12 12:43 | V1003 | 2.8999% | 2.9903% ↑ | 0.7700% | 0.7730% ↑ | 60.0% | 29,019 | ⏭️ Skip |
| 2026-08-12 12:43 | V1009 | 4.0565% | 4.0389% ↓ | 0.6137% | 0.6340% ↑ | 56.2% | 28,881 | ✅ Deploy |
| 2026-08-12 09:43 | V1011 | 8.0090% | 8.1628% ↑ | 3.6571% | 3.7104% ↑ | 18.4% | 28,983 | ⏭️ Skip |
| 2026-08-12 09:43 | V1001 | 5.6851% | 5.6903% ↑ | 3.4222% | 3.4126% ↓ | 5.7% | 28,463 | ✅ Deploy |
| 2026-08-12 09:43 | V1003 | 2.9124% | 3.0561% ↑ | 0.7700% | 0.7723% ↑ | 63.2% | 28,983 | ⏭️ Skip |
| 2026-08-12 09:42 | V1009 | 4.0611% | 4.0523% ↓ | 0.6160% | 0.6252% ↑ | 61.4% | 28,845 | ✅ Deploy |
| 2026-08-12 06:42 | V1011 | 8.0221% | 8.1394% ↑ | 3.6294% | 3.6886% ↑ | 27.6% | 28,947 | ⏭️ Skip |
| 2026-08-12 06:42 | V1001 | 5.6829% | 5.6793% ↓ | 3.4324% | 3.4172% ↓ | 18.1% | 28,427 | ✅ Deploy |
| 2026-08-12 06:42 | V1003 | 2.9093% | 3.0041% ↑ | 0.7702% | 0.7727% ↑ | 63.4% | 28,947 | ⏭️ Skip |
| 2026-08-12 06:42 | V1009 | 4.1206% | 4.0843% ↓ | 0.6212% | 0.6432% ↑ | 61.4% | 28,809 | ✅ Deploy |
| 2026-08-12 03:42 | V1011 | 8.0523% | 8.1914% ↑ | 3.6193% | 3.6455% ↑ | 1.5% | 28,911 | ⏭️ Skip |
| 2026-08-12 03:41 | V1001 | 5.6921% | 5.6871% ↓ | 3.4493% | 3.4468% ↓ | 28.0% | 28,391 | ✅ Deploy |
| 2026-08-12 03:41 | V1003 | 2.9077% | 3.0141% ↑ | 0.7704% | 0.7726% ↑ | 69.5% | 28,911 | ⏭️ Skip |
| 2026-08-12 03:41 | V1009 | 4.1167% | 4.1238% ↑ | 0.6202% | 0.6360% ↑ | 62.3% | 28,773 | ⏭️ Skip |
| 2026-08-12 00:41 | V1011 | 8.0726% | 8.1589% ↑ | 3.6213% | 3.6537% ↑ | 84.8% | 28,875 | ⏭️ Skip |
| 2026-08-12 00:41 | V1001 | 5.7059% | 5.7036% ↓ | 3.4541% | 3.4559% ↑ | 13.4% | 28,355 | ✅ Deploy |
| 2026-08-12 00:41 | V1003 | 2.9055% | 3.0420% ↑ | 0.7717% | 0.7734% ↑ | 62.5% | 28,875 | ⏭️ Skip |
| 2026-08-12 00:41 | V1009 | 4.1160% | 4.1231% ↑ | 0.6253% | 0.6465% ↑ | 58.5% | 28,737 | ⏭️ Skip |
| 2026-08-11 21:41 | V1011 | 8.0869% | 8.2056% ↑ | 3.6252% | 3.6836% ↑ | 87.5% | 28,839 | ⏭️ Skip |
| 2026-08-11 21:40 | V1001 | 5.7011% | 5.7005% ↓ | 3.4669% | 3.4975% ↑ | 21.0% | 28,319 | ✅ Deploy |
কীভাবে কাজ করে
📊
ডেটা সংগ্রহ
প্রতি ৩০ সেকেন্ডে নতুন metrics
📈
Drift শনাক্ত
নতুন vs পুরনো mean (threshold 10%)
🔄
Retrain
XGBoost নতুন ডেটা দিয়ে train
✅
যাচাই
পুরনো vs নতুন RMSE তুলনা
🚀
Deploy
উন্নত হলেই replace