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
6
মোট 50 retrain এর মধ্যে
📉 সর্বশেষ CPU RMSE
4.02%
আগে ছিল: 3.98%
⚡ সর্বশেষ CPU Drift
66.6%
Threshold: 10% · V1009
সর্বশেষ Retrain এর প্রভাব — Real-time Database থেকে
🧠 CPU Forecast — V1009 · 2026-08-13 09:47
আগে
3.98%
RMSE
→
পরে
4.02%
RMSE
1% ↑
খারাপ
Drift: 66.6%
· R²: 0.353 → 0.341
· Samples: 29,134
💾 RAM Forecast — V1009 · 2026-08-13 09:47
আগে
0.61%
RMSE
→
পরে
0.64%
RMSE
5% ↑
খারাপ
RAM Drift: 34.8%
· 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 | V1009 | 3.9841% | 4.0208% ↑ | 0.6120% | 0.6398% ↑ | 66.6% | 29,134 | ⏭️ 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 | V1009 | 4.0139% | 4.0764% ↑ | 0.6061% | 0.6365% ↑ | 63.0% | 29,062 | ⏭️ 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 | V1009 | 4.0354% | 4.1119% ↑ | 0.6087% | 0.6296% ↑ | 60.2% | 28,989 | ⏭️ 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 | V1009 | 4.0505% | 4.0861% ↑ | 0.6074% | 0.6330% ↑ | 51.6% | 28,917 | ⏭️ Skip |
| 2026-08-12 12:43 | V1009 | 4.0565% | 4.0389% ↓ | 0.6137% | 0.6340% ↑ | 56.2% | 28,881 | ✅ Deploy |
| 2026-08-12 09:42 | V1009 | 4.0611% | 4.0523% ↓ | 0.6160% | 0.6252% ↑ | 61.4% | 28,845 | ✅ Deploy |
| 2026-08-12 06:42 | V1009 | 4.1206% | 4.0843% ↓ | 0.6212% | 0.6432% ↑ | 61.4% | 28,809 | ✅ Deploy |
| 2026-08-12 03:41 | V1009 | 4.1167% | 4.1238% ↑ | 0.6202% | 0.6360% ↑ | 62.3% | 28,773 | ⏭️ Skip |
| 2026-08-12 00:41 | V1009 | 4.1160% | 4.1231% ↑ | 0.6253% | 0.6465% ↑ | 58.5% | 28,737 | ⏭️ Skip |
| 2026-08-11 21:40 | V1009 | 4.1421% | 4.1169% ↓ | 0.6304% | 0.6410% ↑ | 39.3% | 28,701 | ✅ Deploy |
| 2026-08-11 18:40 | V1009 | 4.1242% | 4.2109% ↑ | 0.6344% | 0.6488% ↑ | 33.9% | 28,664 | ⏭️ Skip |
| 2026-08-11 15:39 | V1009 | 4.1216% | 4.2097% ↑ | 0.6388% | 0.6591% ↑ | 38.2% | 28,628 | ⏭️ Skip |
| 2026-08-11 12:39 | V1009 | 4.1247% | 4.1923% ↑ | 0.6369% | 0.6492% ↑ | 51.7% | 28,592 | ⏭️ Skip |
| 2026-08-11 09:39 | V1009 | 4.1293% | 4.2086% ↑ | 0.6380% | 0.6568% ↑ | 58.6% | 28,556 | ⏭️ Skip |
| 2026-08-11 06:38 | V1009 | 4.1334% | 4.1620% ↑ | 0.6384% | 0.6523% ↑ | 47.7% | 28,520 | ⏭️ Skip |
| 2026-08-11 03:38 | V1009 | 4.1202% | 4.1656% ↑ | 0.6387% | 0.6627% ↑ | 41.0% | 28,484 | ⏭️ Skip |
| 2026-08-11 00:37 | V1009 | 4.1403% | 4.1481% ↑ | 0.6387% | 0.6514% ↑ | 43.3% | 28,448 | ⏭️ Skip |
| 2026-08-10 21:37 | V1009 | 4.1557% | 4.1365% ↓ | 0.6391% | 0.6662% ↑ | 39.1% | 28,412 | ✅ Deploy |
| 2026-08-10 18:36 | V1009 | 4.1494% | 4.3570% ↑ | 0.6399% | 0.6515% ↑ | 44.8% | 28,376 | ⏭️ Skip |
| 2026-08-10 15:36 | V1009 | 4.1458% | 4.1847% ↑ | 0.6415% | 0.6544% ↑ | 24.7% | 28,340 | ⏭️ Skip |
| 2026-08-10 12:36 | V1009 | 4.1238% | 4.1271% ↑ | 0.6514% | 0.6613% ↑ | 24.0% | 28,304 | ⏭️ Skip |
| 2026-08-10 09:35 | V1009 | 4.1072% | 4.2171% ↑ | 0.6513% | 0.6692% ↑ | 40.6% | 28,268 | ⏭️ Skip |
| 2026-08-10 06:35 | V1009 | 4.1190% | 4.2397% ↑ | 0.6515% | 0.6730% ↑ | 60.2% | 28,231 | ⏭️ Skip |
| 2026-08-10 03:34 | V1009 | 4.1290% | 4.1855% ↑ | 0.6521% | 0.6696% ↑ | 34.2% | 28,195 | ⏭️ Skip |
| 2026-08-10 00:34 | V1009 | 4.1462% | 4.2176% ↑ | 0.6498% | 0.6600% ↑ | 44.6% | 28,159 | ⏭️ Skip |
| 2026-08-09 21:33 | V1009 | 4.1515% | 4.2024% ↑ | 0.6463% | 0.6516% ↑ | 3.2% | 28,123 | ⏭️ Skip |
| 2026-08-09 18:33 | V1009 | 4.1253% | 4.1969% ↑ | 0.6438% | 0.6490% ↑ | 25.0% | 28,087 | ⏭️ Skip |
| 2026-08-09 15:33 | V1009 | 4.1119% | 4.2279% ↑ | 0.6371% | 0.6533% ↑ | 25.2% | 28,051 | ⏭️ Skip |
| 2026-08-09 12:32 | V1009 | 4.0852% | 4.2255% ↑ | 0.6384% | 0.6525% ↑ | 28.5% | 28,015 | ⏭️ Skip |
| 2026-08-09 09:32 | V1009 | 4.0466% | 4.0987% ↑ | 0.6393% | 0.6610% ↑ | 43.7% | 27,979 | ⏭️ Skip |
| 2026-08-09 06:31 | V1009 | 4.0614% | 4.2539% ↑ | 0.6397% | 0.6545% ↑ | 62.9% | 27,943 | ⏭️ Skip |
| 2026-08-09 03:31 | V1009 | 4.0677% | 4.2171% ↑ | 0.6396% | 0.6503% ↑ | 52.0% | 27,907 | ⏭️ Skip |
| 2026-08-09 00:31 | V1009 | 4.1065% | 4.1197% ↑ | 0.6389% | 0.6636% ↑ | 49.9% | 27,871 | ⏭️ Skip |
| 2026-08-08 21:30 | V1009 | 4.1067% | 4.2138% ↑ | 0.6374% | 0.6534% ↑ | 22.6% | 27,835 | ⏭️ Skip |
| 2026-08-08 18:30 | V1009 | 4.1140% | 4.1846% ↑ | 0.6340% | 0.6511% ↑ | 33.2% | 27,799 | ⏭️ Skip |
| 2026-08-08 15:30 | V1009 | 4.1468% | 4.2151% ↑ | 0.6345% | 0.6455% ↑ | 36.2% | 27,762 | ⏭️ Skip |
| 2026-08-08 12:29 | V1009 | 4.1471% | 4.2105% ↑ | 0.6350% | 0.6600% ↑ | 50.0% | 27,726 | ⏭️ Skip |
| 2026-08-08 09:29 | V1009 | 4.1450% | 4.1647% ↑ | 0.6356% | 0.6539% ↑ | 46.5% | 27,690 | ⏭️ Skip |
| 2026-08-08 06:29 | V1009 | 4.1346% | 4.1392% ↑ | 0.6371% | 0.6534% ↑ | 56.5% | 27,654 | ⏭️ Skip |
| 2026-08-08 03:28 | V1009 | 4.1407% | 4.1838% ↑ | 0.6375% | 0.6543% ↑ | 22.1% | 27,618 | ⏭️ Skip |
| 2026-08-08 00:28 | V1009 | 4.1479% | 4.1861% ↑ | 0.6341% | 0.6457% ↑ | 44.1% | 27,582 | ⏭️ Skip |
| 2026-08-07 21:27 | V1009 | 4.1525% | 4.2621% ↑ | 0.6326% | 0.6514% ↑ | 37.6% | 27,546 | ⏭️ Skip |
| 2026-08-07 18:27 | V1009 | 4.1553% | 4.2146% ↑ | 0.6304% | 0.6434% ↑ | 47.9% | 27,510 | ⏭️ Skip |
| 2026-08-07 15:26 | V1009 | 4.1582% | 4.1632% ↑ | 0.6277% | 0.6389% ↑ | 48.2% | 27,474 | ⏭️ Skip |
| 2026-08-07 12:26 | V1009 | 4.1963% | 4.1590% ↓ | 0.6305% | 0.6537% ↑ | 52.5% | 27,438 | ✅ Deploy |
| 2026-08-07 09:25 | V1009 | 4.1950% | 4.2405% ↑ | 0.6328% | 0.6582% ↑ | 47.2% | 27,401 | ⏭️ Skip |
| 2026-08-07 06:24 | V1009 | 4.1904% | 4.2425% ↑ | 0.6343% | 0.6518% ↑ | 52.0% | 27,365 | ⏭️ Skip |
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