**Clustering Algorithms MCQs**

1. Which of the following is a goal of clustering algorithms?

a. Classification

b. Regression

c. Dimensionality reduction

d. Grouping similar data points together

Answer: d. Grouping similar data points together

2. Which clustering algorithm is based on the concept of centroids?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

3. Which clustering algorithm does not require specifying the number of clusters in advance?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

4. Which clustering algorithm is sensitive to the order of the data points?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: d. Mean-Shift

5. Which clustering algorithm is based on a density-based approach?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

6. Which clustering algorithm uses a hierarchical approach to create clusters?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: c. Agglomerative

7. Which clustering algorithm is based on the concept of medoids?

a. K-Means

b. DBSCAN

c. Agglomerative

d. K-Medoids

Answer: d. K-Medoids

8. Which clustering algorithm is capable of detecting outliers as noise points?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

9. Which clustering algorithm is suitable for non-linearly separable data?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: d. Mean-Shift

10. Which clustering algorithm assigns data points to the nearest cluster centroid?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

11. Which clustering algorithm is computationally efficient for large datasets?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

12. Which clustering algorithm can handle clusters of varying shapes and sizes?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

13. Which clustering algorithm does not require the assumption of equal-sized clusters?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: d. Mean-Shift

14. Which clustering algorithm is based on the concept of nearest neighbors?

a. K-Means

b. DBSCAN

c. Agglomerative

d. K-Nearest Neighbors

Answer: d. K-Nearest Neighbors

15. Which clustering algorithm is sensitive to the initial placement of cluster centroids?

a. K-Means

b

. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

16. Which clustering algorithm is based on the concept of minimizing the within-cluster variance?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

17. Which clustering algorithm is suitable for high-dimensional data?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

18. Which clustering algorithm is capable of identifying dense regions in the data?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

19. Which clustering algorithm is based on the concept of similarity or distance between data points?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

20. Which clustering algorithm can handle categorical data?

a. K-Means

b. DBSCAN

c. Agglomerative

d. K-Modes

Answer: d. K-Modes

21. Which clustering algorithm is based on the concept of density-reachable points?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

22. Which clustering algorithm is capable of handling noise and outliers effectively?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: b. DBSCAN

23. Which clustering algorithm is suitable for time-series data?

a. K-Means

b. DBSCAN

c. Agglomerative

d. K-Shape

Answer: d. K-Shape

24. Which clustering algorithm is based on the concept of merging the closest clusters iteratively?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: c. Agglomerative

25. Which clustering algorithm is suitable for large datasets with an unknown number of clusters?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: d. Mean-Shift

26. Which clustering algorithm is based on the concept of fuzzy sets and membership degrees?

a. K-Means

b. DBSCAN

c. Fuzzy C-Means

d. Mean-Shift

Answer: c. Fuzzy C-Means

27. Which clustering algorithm can be used to identify overlapping clusters in the data?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Density-Based Overlapping Clustering

Answer: d. Density-Based Overlapping Clustering

28. Which clustering algorithm is based on the concept of minimizing the sum of squared errors within each cluster?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: a. K-Means

29. Which clustering algorithm is suitable for text mining and document clustering?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Latent Dirichlet

Allocation (LDA)

Answer: d. Latent Dirichlet Allocation (LDA)

30. Which clustering algorithm is suitable for image segmentation and object detection?

a. K-Means

b. DBSCAN

c. Agglomerative

d. Mean-Shift

Answer: d. Mean-Shift