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
5
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 06:46 | V1011 | 7.9573% | 8.0358% ↑ | 3.6659% | 3.7113% ↑ | 87.6% | 29,236 | ⏭️ Skip |
| 2026-08-13 03:46 | V1011 | 7.9743% | 8.1042% ↑ | 3.6561% | 3.7109% ↑ | 50.0% | 29,200 | ⏭️ Skip |
| 2026-08-13 00:46 | V1011 | 7.9744% | 8.0717% ↑ | 3.6584% | 3.7050% ↑ | 21.8% | 29,164 | ⏭️ Skip |
| 2026-08-12 21:45 | V1011 | 7.9971% | 8.1023% ↑ | 3.6608% | 3.6925% ↑ | 22.6% | 29,127 | ⏭️ Skip |
| 2026-08-12 18:45 | V1011 | 8.0134% | 8.0984% ↑ | 3.6631% | 3.6811% ↑ | 5.7% | 29,091 | ⏭️ Skip |
| 2026-08-12 15:44 | V1011 | 8.0108% | 8.1107% ↑ | 3.6704% | 3.7282% ↑ | 10.2% | 29,055 | ⏭️ Skip |
| 2026-08-12 12:44 | V1011 | 8.0066% | 8.1698% ↑ | 3.6622% | 3.6980% ↑ | 13.0% | 29,019 | ⏭️ Skip |
| 2026-08-12 09:43 | V1011 | 8.0090% | 8.1628% ↑ | 3.6571% | 3.7104% ↑ | 18.4% | 28,983 | ⏭️ Skip |
| 2026-08-12 06:42 | V1011 | 8.0221% | 8.1394% ↑ | 3.6294% | 3.6886% ↑ | 27.6% | 28,947 | ⏭️ Skip |
| 2026-08-12 03:42 | V1011 | 8.0523% | 8.1914% ↑ | 3.6193% | 3.6455% ↑ | 1.5% | 28,911 | ⏭️ Skip |
| 2026-08-12 00:41 | V1011 | 8.0726% | 8.1589% ↑ | 3.6213% | 3.6537% ↑ | 84.8% | 28,875 | ⏭️ Skip |
| 2026-08-11 21:41 | V1011 | 8.0869% | 8.2056% ↑ | 3.6252% | 3.6836% ↑ | 87.5% | 28,839 | ⏭️ Skip |
| 2026-08-11 18:40 | V1011 | 8.1246% | 8.2188% ↑ | 3.6283% | 3.6738% ↑ | 53.4% | 28,802 | ⏭️ Skip |
| 2026-08-11 15:39 | V1011 | 8.1388% | 8.2109% ↑ | 3.6324% | 3.6948% ↑ | 7.1% | 28,766 | ⏭️ Skip |
| 2026-08-11 12:39 | V1011 | 8.1341% | 8.2077% ↑ | 3.6339% | 3.6774% ↑ | 4.7% | 28,730 | ⏭️ Skip |
| 2026-08-11 09:39 | V1011 | 8.1490% | 8.2476% ↑ | 3.6359% | 3.6675% ↑ | 33.7% | 28,694 | ⏭️ Skip |
| 2026-08-11 06:39 | V1011 | 8.1541% | 8.2577% ↑ | 3.6184% | 3.6556% ↑ | 13.2% | 28,658 | ⏭️ Skip |
| 2026-08-11 03:38 | V1011 | 8.1819% | 8.2222% ↑ | 3.5993% | 3.6233% ↑ | 103.4% | 28,622 | ⏭️ Skip |
| 2026-08-11 00:38 | V1011 | 8.2261% | 8.2999% ↑ | 3.6034% | 3.6509% ↑ | 51.2% | 28,586 | ⏭️ Skip |
| 2026-08-10 21:37 | V1011 | 8.2343% | 8.3021% ↑ | 3.6023% | 3.6271% ↑ | 66.7% | 28,550 | ⏭️ Skip |
| 2026-08-10 18:36 | V1011 | 8.2274% | 8.3196% ↑ | 3.5928% | 3.6113% ↑ | 1.2% | 28,514 | ⏭️ Skip |
| 2026-08-10 15:36 | V1011 | 8.2463% | 8.3470% ↑ | 3.5622% | 3.5699% ↑ | 37.1% | 28,478 | ⏭️ Skip |
| 2026-08-10 12:36 | V1011 | 8.2620% | 8.3361% ↑ | 3.4952% | 3.5161% ↑ | 45.8% | 28,442 | ⏭️ Skip |
| 2026-08-10 09:35 | V1011 | 8.2801% | 8.3288% ↑ | 3.4490% | 3.4939% ↑ | 35.6% | 28,406 | ⏭️ Skip |
| 2026-08-10 06:35 | V1011 | 8.3036% | 8.3368% ↑ | 3.3792% | 3.4279% ↑ | 63.9% | 28,370 | ⏭️ Skip |
| 2026-08-10 03:35 | V1011 | 8.3344% | 8.4546% ↑ | 3.3609% | 3.3850% ↑ | 30.3% | 28,333 | ⏭️ Skip |
| 2026-08-10 00:34 | V1011 | 8.3588% | 8.4336% ↑ | 3.3654% | 3.3645% ↓ | 57.7% | 28,297 | ✅ Deploy |
| 2026-08-09 21:34 | V1011 | 8.4014% | 8.4306% ↑ | 3.3681% | 3.4064% ↑ | 79.2% | 28,261 | ⏭️ Skip |
| 2026-08-09 18:33 | V1011 | 8.4256% | 8.4270% ↑ | 3.3729% | 3.4409% ↑ | 87.0% | 28,225 | ⏭️ Skip |
| 2026-08-09 15:33 | V1011 | 8.4371% | 8.5064% ↑ | 3.3749% | 3.4091% ↑ | 40.4% | 28,189 | ⏭️ Skip |
| 2026-08-09 12:32 | V1011 | 8.4378% | 8.4709% ↑ | 3.3746% | 3.4239% ↑ | 45.0% | 28,153 | ⏭️ Skip |
| 2026-08-09 09:32 | V1011 | 8.4488% | 8.4866% ↑ | 3.3743% | 3.3781% ↑ | 5.4% | 28,117 | ⏭️ Skip |
| 2026-08-09 06:32 | V1011 | 8.4937% | 8.5361% ↑ | 3.3729% | 3.4097% ↑ | 24.0% | 28,081 | ⏭️ Skip |
| 2026-08-09 03:31 | V1011 | 8.5118% | 8.5299% ↑ | 3.3557% | 3.3836% ↑ | 33.0% | 28,045 | ⏭️ Skip |
| 2026-08-09 00:31 | V1011 | 8.5463% | 8.5744% ↑ | 3.3458% | 3.3793% ↑ | 32.2% | 28,009 | ⏭️ Skip |
| 2026-08-08 21:30 | V1011 | 8.5698% | 8.5896% ↑ | 3.3502% | 3.4127% ↑ | 30.0% | 27,973 | ⏭️ Skip |
| 2026-08-08 18:30 | V1011 | 8.5985% | 8.6113% ↑ | 3.3528% | 3.3944% ↑ | 4.3% | 27,937 | ⏭️ Skip |
| 2026-08-08 15:30 | V1011 | 8.6297% | 8.6608% ↑ | 3.3454% | 3.3939% ↑ | 57.4% | 27,901 | ⏭️ Skip |
| 2026-08-08 12:30 | V1011 | 8.6470% | 8.6621% ↑ | 3.2620% | 3.3198% ↑ | 57.4% | 27,864 | ⏭️ Skip |
| 2026-08-08 09:29 | V1011 | 8.6547% | 8.6955% ↑ | 3.1855% | 3.2346% ↑ | 59.5% | 27,828 | ⏭️ Skip |
| 2026-08-08 06:29 | V1011 | 8.6686% | 8.7034% ↑ | 3.1056% | 3.1382% ↑ | 45.2% | 27,792 | ⏭️ Skip |
| 2026-08-08 03:28 | V1011 | 8.7073% | 8.6852% ↓ | 3.0855% | 3.1250% ↑ | 64.0% | 27,756 | ✅ Deploy |
| 2026-08-08 00:28 | V1011 | 8.7442% | 8.7294% ↓ | 3.0873% | 3.1354% ↑ | 3.1% | 27,720 | ✅ Deploy |
| 2026-08-07 21:28 | V1011 | 8.7701% | 8.7554% ↓ | 3.0837% | 3.0937% ↑ | 61.4% | 27,684 | ✅ Deploy |
| 2026-08-07 18:27 | V1011 | 8.8198% | 8.7772% ↓ | 3.0797% | 3.0905% ↑ | 44.0% | 27,648 | ✅ Deploy |
| 2026-08-07 15:27 | V1011 | 8.8194% | 8.8297% ↑ | 3.0961% | 3.1271% ↑ | 57.0% | 27,612 | ⏭️ Skip |
| 2026-08-07 12:26 | V1011 | 8.8276% | 8.8676% ↑ | 3.0195% | 3.0441% ↑ | 62.0% | 27,576 | ⏭️ Skip |
| 2026-08-07 09:26 | V1011 | 8.8494% | 8.9350% ↑ | 3.0194% | 3.1235% ↑ | 89.3% | 27,540 | ⏭️ Skip |
| 2026-08-07 06:25 | V1011 | 8.8885% | 8.9542% ↑ | 3.0218% | 3.0478% ↑ | 71.5% | 27,503 | ⏭️ 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