Hababka Isku-dhafka ah iyo Kediska Kobcinta Dareenka

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay hawlgalka asaasiga ah ee habka isku-dhafka?
   • Combining predictions from multiple models
   • Isticmaalka hal nooc oo aad u weyn halkii aad ka isticmaali lahayd kuwa yaryar oo badan
   • Ku tababbaridda tusaalaha xogta ugu badan ee suurtogalka ah
   • Ka saarida dhammaan bartayaasha daciifka ah moodalka
2. Sidee buu kor u qaadida gradient uga duwan yahay boorsada habka tababarka caadiga ah?
   • Kobcinta waxay tabobaraysaa geedaha is barbar socda; boorsooyinka ayaa si isdaba joog ah u tababara
   • Boosting adds learners sequentially; independently fitted bagging learners can be trained in parallel
   • Kobcinta waxay ku shaqeysaa kaliya sawirada; baaritaannada qoraalka kaliya
   • Dhaqan ahaan waa isku mid
3. Kor u qaadis tartiib tartiib ah, waa maxay bartilmaameedka geedka cusub ku qiyaasaa?
   • Calaamadaha asalka ah ee cayriin
   • Qayb hoose oo random ah oo sifooyinka kaliya ah
   • The negative gradient of the current loss, often called a pseudo-residual
   • Celceliska dhammaan geedihii hore
4. Waa maxay saamaynta suurtogalka ah ee isticmaalka heerka waxbarashada yar ee kor u qaadista?
   • Si loo kordhiyo cabbirka geed kasta
   • Si loo tirtiro geedaha si liidata u shaqeeya
   • Si geedaha loogu badalo shabakadaha neerfaha
   • It can make updates more gradual and may require more trees
5. Nooc noocee ah ayaa lagu isticmaalaa tusaalooyinka iyo daraasadaha geedka- gradient-kobciyay?
   • Structured or tabular data
   • Sawirro heer sare ah
   • Qaababka mowjadaha codka qaydhiin
   • Dukumentiyada luqadda dabiiciga ah ee dhaadheer
6. Waa kuwee farsamada caadiga ah ee loo isticmaalo in laga ilaaliyo kor u kaca?
   • Ka saarida shaqada khasaaraha
   • Xakamaynta qoto dheer ee geedka iyo qaybinta safafka/ sifooyinka
   • Isticmaalka heerka waxbarasho ee saxda ah 1.0 had iyo jeer
   • Tababar aan la koobi karin oo geedo badan
7. What does an out-of-bag score estimate in a bagged tree ensemble?
   • The accuracy on examples used by every tree
   • The number of leaves in the largest tree
   • Generalization performance using training examples omitted from a tree’s bootstrap sample
   • The learning rate of a gradient-boosted model
8. What does early stopping monitor during gradient-boosting training?
   • Only the training-set row order
   • Whether the model has no trees left
   • The number of categorical columns in a spreadsheet
   • A validation metric and stops adding trees when it no longer improves