Model Drift Detection Quiz

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

1. Ndeupi musiyano uripo pakati pe data drift uye concept drift?
   • Kudhiriwa kwedata kunoshandura kugovera kwezvinopinza; concept drift inoshandura hukama hwekupinza-ku-kubuda
   • Ndiwo mazita maviri echinhu chimwe chete
   • Data drift inokanganisa mifananidzo chete; concept drift inokanganisa zvinyorwa chete
   • Data drift inoitika mukudzidziswa; concept drift inoitika mukuyedzwa
2. How should a team interpret a PSI value such as 0.30?
   • As a guarantee that model accuracy has fallen
   • As a signal to investigate under the chosen monitoring policy, not a universal proof of harmful drift
   • As an identical threshold for every feature and population
   • As proof that retraining must begin immediately
3. Sei kupinza-kwakavakirwa kuona kukukurwa kuchigona kupa yambiro nekukurumidza?
   • Nekuti zvekupinza zvinogara zvisirizvo kutanga
   • Nekuti zvekupinza madiki mafaera
   • Nekuti mavara echokwadi-pasi anowanzosvika pave paya pane zvakafanotaurwa
   • Nekuti mamodheru anofuratira mavara zvachose
4. What does a two-sample Kolmogorov-Smirnov test compare?
   • The average accuracy of two classifiers only
   • The class labels predicted by a single model
   • The parameter values of two neural networks
   • The empirical cumulative distribution functions of two samples
5. Ndeipi mamiriro emuenzaniso wakajeka wepfungwa yekudonha?
   • Izvo vashandisi vanofunga nezve 'spam' zvinoshanduka nekufamba kwenguva kunyangwe kune maemail akafanana
   • Kamera inogadzira mifananidzo inopenya zvishoma
   • Mazera emutengi ari mudataset anoramba akafanana
   • Iyo dataset inochengetwa mune nyowani faira fomati
6. What is a safe first response when an input-drift monitor triggers?
   • Automatically deploy a newly retrained model without evaluation
   • Investigate the data and impact, then decide whether retraining or another action is justified
   • Delete the reference data
   • Assume every shift is harmful concept drift
7. What can TensorFlow Data Validation check in an ML pipeline?
   • The causal effect of a feature
   • Whether every model prediction is correct
   • Data schemas and statistics, including unexpected changes
   • The absolute accuracy of an unlabeled dataset
8. What does the Population Stability Index (PSI) measure in a drift-monitoring setup?
   • The model’s accuracy on labeled examples
   • A causal effect of an input feature
   • A universal pass/fail threshold for all models
   • A numerical summary of how binned feature distributions differ between reference and current data