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