quiz bu lëkkale ak tegtal · Diggante Niveau
Quiz ngir gis model drift
Xoolaat done ak konsept drift, di wottu séddale, KS méngale, etiket yu yeex, ak tontu yu jaar yoon ci drift alarm.
Laaj 1 de 8
Lan mooy wuutale derifu done ak derifu konsept?
Xoolaatal laaj bu nekk8 laaj
Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.
- Lan mooy wuutale derifu done ak derifu konsept?
- Drift done yi dafay soppi séddaleb done yi; konsept drift dafay soppi diggante dugal ak genn
- Ñaari tur lañu ngir benn mbir
- Done drift du am njeexital ci nataal yi kese; konsept drift du am njeexital ci bind
- Data drift dafay am ci tàggat yaram; konsept drift dafay am ci test
- 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
- Lan moo waral gis-gis bi lalu ci dugal mën na teela artu?
- Ndax dugal yi dañuy njëkka juum
- Ndax dugal yi dañu gëna ndaw
- Ndax etiketu dëgg yi dañuy faral di ñëw ginaaw li ñu séentuwoon
- Ndax model yi duñu bàyyi xel ci etiket yi
- 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
- Ban senaario mooy misaalu drift konsept bu leer?
- Li jëfandikukat yi jàpp ni 'spam' dafay soppeeku lu yàgg doonte ci imeel yu nuru
- Kamera dafay defar nataal yu gëna leer tuuti
- Jamono kiliyaan yi ci done yi duñu soppeeku
- Dañu denc done yi ci formaa fichier bu bees
- 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
- 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
- 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