Isku dheelitir la'aanta fasalka iyo Kediska Dib-u-qaadista

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay sababta saxnaanta cad u tahay mitir liidata ee dhibaatada soocidda aadka u dheelitiran?
   • Qaabku waxa uu dhalin karaa mid aad u sareeya kaliya isagoo had iyo jeer saadaaliya fasalka aqlabiyada
   • Saxnimada lama xisaabin karo marka fasalladu isku dheeli tiran yihiin
   • Xaqiijintu waxay kaliya u shaqeysaa dib u noqoshada
   • Waxay u baahan tahay xog dheeli tiran si loo qeexo
2. Muxuu sameeyaa SMOTE?
   • Tirtiraa shaybaarada heerka ugu badan si aan kala sooc lahayn
   • Wuxuu abuuraa muunado laga tiro badan yahay oo la isku-dhafan isagoo is-dhex-galiya deriska
   • Waxay kordhisaa heerka waxbarasho ee fasallada dhifka ah
   • U beddelo dhibaatada kala soocida dib u noqosho
3. Habka kee u maareeya dheelitir la'aanta IYADOO aan la beddelin tirada tusaalooyinka tababarka?
   • Naqshadeynta aan tooska ahayn
   • Fahminta aqlabiyadda
   • Miisaanka fasalka ee shaqada lumin
   • SMOTE
4. Waa maxay khatarta muhiimka ah ee isticmaalka xad-dhaafka ah ka hor inta aanad xogtaada u kala qaybin tareenka iyo qaybaha tijaabada?
   • Waxay ka dhigtaa tababarka mid gaabis ah
   • Waxay tirtirtaa fasalka aqlabiyadda
   • Had iyo jeer waxay keentaa hoos u dhac
   • Dhibcaha laga tirada badan yahay ee la soo koobay ama synthetic waxay ku daadan karaan imtixaanka, buundooyinka buunbuuninayaa
5. Waa maxay faa'iidada ugu weyn ee sampling-yarida random?
   • Waxay tuuraysaa xogta laga yaabo inay faa'iido u leedahay inta badan
   • Waxay abuurtaa xog been abuur ah oo laga yaabo inay noqoto mid aan dhab ahayn
   • Waxay u shaqeysaa oo kaliya xogta sawirka
   • Had iyo jeer waxay kordhisaa wakhtiga tababarka
6. Halbeegkee ayaa ugu habboon in lagu qiimeeyo tusaalaha xogta dhifka ah ee togan?
   • Saxnaanta guud
   • Saxnaanta-Recall AUC ama F1 dhibcood
   • Khalad afar gees leh celcelis ahaan
   • Tirada waayaha tababarka
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)