quiz bu lëkkale ak tegtal · Diggante Niveau

Déséquilibre ci klaas bi ak quiz buy jël misaal

Dafay saytu kañ lañu wara jëlaat misaal wala jëlaat poñ yi ci klaas yu bariwul yi, naka la fuite done di amee, ak ban metrics mooy des am njariñ ci desekilibre klaas.

Yooni njiit yu jëm ciDéséquilibre ci klaas yi ak jëlaat échantillonnage
Laaj 1 de 8

Lan moo waral njubte bu leer nekkul metrik bu baaxul ci jafe-jafe xaaj bu jaxasoo lool?

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  1. Lan moo waral njubte bu leer nekkul metrik bu baaxul ci jafe-jafe xaaj bu jaxasoo lool?
    • Benn model mën na am poñ yu bari sudee dafay wax luy waaja am ci klaas bi gëna bari
    • Mënu xayma njub sudee klaas yi tolloowul
    • Jaar-jaar du dox ludul ci regression
    • Dafay laaj done yu ekilibre bu baax ngir mëna joxe leeral
  2. Luy SMOTE?
    • efaase misaali klaas yu bari ci anam wu mucc
    • Defar ay misaali sintetik yu néew ci interpolaasioŋ ci diggante dëkkandoo yi
    • Yokk limu jàng ci klaas yu bariwul
    • Dafay soppi jafe-jafe xaaj ci régression
  3. Ban gis-gis mooy saafara jafe-jafe te du soppi limu misaali tàggat yi?
    • Exéchantillonnage aléatoire
    • Sampling bu néew
    • Pondération classe ci fonction perte
    • SMOTE
  4. Lan mooy risk bu mag bi ci jëfandikoo oversampling balaa ngay xaaj say done ci saxaar ak ensemble test?
    • Dafay yeexal tàggat yaram
    • Dafay efaase klaas bi gëna bari
    • Dafay faral di indi ñàkka mëna ànd
    • Ñaari yoon wala ñu defar ay poñ yu néew mën nañu dugg ci test bi, di yokk poñ yi
  5. Lan mooy jafe-jafe bi gëna mag ci sampling bu bariwul?
    • Dafay sànni done yu gëna am njariñ
    • Dafay sos ay done yu baaxul yu mën nekk lu amul benn dëgg
    • Dafay dox ludul ci done nataal
    • Dafay yokk saa yu nekk ci diiru tàggat yaram
  6. Ban metrik moo gëna baax ngir jàngat xeetu done yu bariwul ñu am?
    • Jaar-jaar bu mat sëkk
    • Njortu AUC wala F1
    • Jumtukaay kaare moyen
    • Limu jamonoy tàggat yaram
  7. What does adjusting the decision threshold after training change?
    • The number of features in the model
    • The class proportions in the training data
    • The trade-off between which examples are labeled positive and negative without changing the training examples
    • The model’s learned weights automatically
  8. Which metric does the guide name as an additional option for rare-positive classification?
    • Mean squared error only
    • BLEU score
    • Silhouette coefficient
    • Matthews Correlation Coefficient (MCC)