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