K-Means Quiz buy boole

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

1. Luy 'K' bi ci K-Means?
   • Limu cluster yi nga tànn bu njëkk
   • Limu poñ yiñ joxe
   • Limu iterasioŋ yi ci tàggat yaram
   • Limu man-man yi ci done yi
2. Lan mooy ñaari jéego yi ñuy baamtu ci bouclage K-Means bi?
   • Xaajaleel cluster yi, nga boole cluster yi
   • Jox poñ yi centroid bi gëna jege, nga toxal centroid yi ci moyenne bi
   • Etiketu done yi, ba noppi tàggat ab xaajkat
   • Tànntal done yi, ba noppi dindi li génn
3. Ban limu K-Means di jéema wàññi?
   • limu cluster yi
   • Diggante centroid yi
   • Distance carrée ci biir mbooloo (inertie)
   • Limu man-man yi
4. Lu tax ñuy woowe K-Means algorithm buñu 'dul saytu'?
   • It uses predefined class labels to learn a boundary
   • It requires one label per initial centroid
   • It estimates labels only after supervised training
   • It groups inputs without target class labels
5. Lan mooy 'méthode concou' bi ñuy faral di jëfandikoo?
   • Gaawaale tàggat yaram
   • Tann valeur bu baax ci K
   • Centroid yiy tàmbali
   • Dindi ñaari poñ
6. Lan moo waral K-Means mëna joxe ay resultaa yu wuute ci daw yu wuute?
   • K automatically changes on every run
   • Euclidean distance uses a random definition
   • Results depend on initial centroid positions
   • Convergence always produces the same global optimum
7. A K-Means cluster contains the one-dimensional values 2, 4, and 9. Where does its centroid move in the update step?
   • 5, the mean of the assigned values
   • 4, the middle observed value
   • 9, the largest assigned value
   • 15, the sum of the assigned values
8. A dataset contains two long, curved groups. Which K-Means limitation should the analyst consider?
   • The groups must have labels before clustering
   • K-Means always discovers curved boundaries exactly
   • Changing K guarantees the intended grouping
   • Euclidean distance to centroids can poorly represent elongated or non-spherical groups