Idanwo Iwari Anomaly AI

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. Kini idi ti wiwa anomaly nigbagbogbo n ṣiṣẹ laisi awọn apẹẹrẹ aami ti awọn asemase?
   • Anomalies jẹ toje ati airotẹlẹ, nitorinaa awọn awoṣe kọ ẹkọ 'deede' dipo
   • Awọn aami jẹ arufin lati lo
   • Anomalies ko ṣẹlẹ
   • O nlo awọn aworan nikan
2. A 'contextual anomaly' jẹ aaye data kan ti o jẹ:
   • Nigbagbogbo ajeji nibi gbogbo
   • Deede ni ipo kan ṣugbọn ajeji ni omiiran
   • A typo ni a database
   • Igbasilẹ ẹda-iwe kan
3. What does the cited WACV autoencoder study use as an anomaly score?
   • A legal fraud label assigned to every record
   • A guarantee that no future fault will occur
   • Reconstruction error from an autoencoder trained to model the data
   • The number of random trees in an Isolation Forest
4. How does the original Isolation Forest paper isolate candidate anomalies?
   • It requires an expert to label every anomaly in advance
   • It measures reconstruction error from a neural decoder
   • It uses a fixed threshold that proves an item is defective
   • Random partitioning tends to isolate anomalous instances in fewer splits
5. Kini ewu akọkọ ti ṣiṣeto iloro alaiṣedeede ju ni ifarabalẹ?
   • Awọn atunnkanka gba ikun omi pẹlu awọn itaniji eke
   • Awọn awoṣe nṣiṣẹ yiyara
   • Data olubwon ti paroko
   • Anomalies di soro
6. What can an unusual machine-vibration score reasonably trigger?
   • An automatic shutdown because failure is guaranteed
   • A maintenance investigation or additional measurement, without predicting failure with certainty
   • A confirmed diagnosis of the failed component
   • A claim that the machine will fail within a fixed number of hours
7. Why is an anomaly score not automatically a fraud or defect label?
   • It is always a verified label
   • Anomaly scores cannot be compared
   • It indicates unusualness under a model or baseline, not the cause or consequence
   • The threshold proves intent
8. What should be documented when setting an anomaly threshold?
   • Only the model’s name
   • A claim that false positives are impossible
   • The number of GPUs alone
   • The reference data, score definition, threshold rationale, and review process