MCQs

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Overall MCQs for Reference

1. What is the main purpose of grouping in machine learning?
   a. Prediction
   b. Supervised learning
   c. Classification
   d. Identifying structure in unlabeled data
   Answer: d. Identifying structure in unlabeled datageeksforgeeks+1​
2. Which algorithm is primarily used for grouping similar data points?
   a. Regression
   b. K-Means
   c. Decision tree
   d. Random forest
   Answer: b. K-Meansaimcqs+1​
3. In unsupervised learning, what type of problem does grouping help address?
   a. Clustering
   b. Labeling
   c. Regression
   d. Classification
   Answer: a. Clusteringmlexam+1​
4. What is the process of dividing unlabeled data into distinct groups called?
   a. Regression
   b. Clustering
   c. Dimensionality reduction
   d. Classification
   Answer: b. Clusteringgeeksforgeeks+1​
5. Which clustering algorithm is based on density?
   a. K-Means
   b. DBSCAN
   c. Linear regression
   d. Logistic regression
   Answer: b. DBSCANaimcqs+1​
6. What is the initial step in hierarchical clustering?
   a. Assign all data to a single cluster
   b. Assign each data point to its own cluster
   c. Specify cluster count
   d. Select distance metric
   Answer: b. Assign each data point to its own clusteryoutube​aimcqs​
7. What is a dendrogram used for in clustering?
   a. Classification rules
   b. Visualization of data groups
   c. Model accuracy measurement
   d. Regression analysis
   Answer: b. Visualization of data groupsscribd+1​
8. Which clustering method does not require specifying the number of clusters?
   a. Agglomerative
   b. K-Means
   c. Mean-Shift
   d. Regression
   Answer: c. Mean-Shiftmlexam+1​
9. What is the role of distance measures in clustering?
   a. Define feature importance
   b. Calculate model loss
   c. Determine similarity between data points
   d. Assign labels
   Answer: c. Determine similarity between data pointsgithub+1​
10. Which algorithm works by iteratively merging the closest clusters?
    a. Divisive clustering
    b. K-Means
    c. Agglomerative clustering
    d. DBSCAN
    Answer: c. Agglomerative clusteringgithub+1​
11. Which one is NOT a clustering algorithm?
    a. Spectral clustering
    b. K-Nearest Neighbor
    c. DBSCAN
    d. K-Medoids
    Answer: b. K-Nearest Neighboraimcqs+1​
12. What does “grouping” in machine learning typically refer to?
    a. Creating labeled datasets
    b. Identifying clusters in unlabeled data
    c. Reducing data dimensionality
    d. Maximizing regression accuracy
    Answer: b. Identifying clusters in unlabeled datageeksforgeeks+1​
13. What would clustering algorithms most commonly be used for?
    a. Customer segmentation
    b. Binary classification
    c. Time series forecasting
    d. Regression tasks
    Answer: a. Customer segmentationgithub+1​
14. Which linkage criterion calculates the shortest distance between clusters in hierarchical clustering?
    a. Single linkage
    b. Complete linkage
    c. Average linkage
    d. Ward linkage
    Answer: a. Single linkagealmabetter+1​
15. Which property describes an ideal cluster?
    a. Overlapping groups
    b. Well-separated and compact clusters
    c. Variable cluster density
    d. High model bias
    Answer: b. Well-separated and compact clusterssanfoundry​youtube​
16. Which clustering method starts with all data in one cluster and recursively splits it?
    a. Agglomerative clustering
    b. Divisive clustering
    c. K-Means clustering
    d. DBSCAN
    Answer: b. Divisive clusteringscribd+1​
17. What does the K in K-Means denote?
    a. Number of clusters
    b. Iterations
    c. Centroid location
    d. Feature dimension
    Answer: a. Number of clustersyoutube​aimcqs​
18. What is silhouette score?
    a. Classification metric
    b. Regression evaluation
    c. Measure of cluster quality
    d. Feature selection method
    Answer: c. Measure of cluster qualitymlexam+1​
19. Which method does NOT use distance between clusters?
    a. Agglomerative clustering
    b. K-Means clustering
    c. DBSCAN
    d. Decision tree
    Answer: d. Decision treesanfoundry+1​
20. What is a core concept for grouping in unsupervised machine learning?
    a. Label assignment
    b. Maximizing distance
    c. Similarity measurement
    d. Feature encoding
    Answer: c. Similarity measurementgithub+1​
21. Which clustering algorithm can detect arbitrarily shaped clusters?
    a. K-Means
    b. DBSCAN
    c. Agglomerative
    d. Mean-Shift
    Answer: b. DBSCANstudyglance+1​
22. Which metric is commonly used for measuring distance in clustering?
    a. Accuracy
    b. F1-score
    c. Euclidean distance
    d. ROC curve
    Answer: c. Euclidean distancemlexam+1​
23. Which clustering method is suitable for very large datasets due to its linear time complexity?
    a. DBSCAN
    b. K-Means
    c. Divisive clustering
    d. Spectral clustering
    Answer: b. K-Meansscribd+1​
24. In hierarchical clustering, what does cutting the dendrogram at a certain level achieve?
    a. Reduces data features
    b. Determines cluster count
    c. Assigns supervised labels
    d. Splits features
    Answer: b. Determines cluster countscribd+1​
25. Which technique groups data based on density of points in space?
    a. Agglomerative clustering
    b. Spectral clustering
    c. DBSCAN
    d. Mean-Shift
    Answer: c. DBSCANstudyglance+1​
26. Which grouping method is commonly used for text document similarity?
    a. K-Means
    b. Agglomerative clustering
    c. DBSCAN
    d. Mean-Shift
    Answer: a. K-Meansgithub+1​
27. Which property should a cluster NOT have?
    a. High intra-cluster similarity
    b. Low inter-cluster similarity
    c. Large variation within the cluster
    d. Compact shape
    Answer: c. Large variation within the clustergeeksforgeeks+1​
28. In K-Means, what is recalculated after each iteration?
    a. Data labels
    b. Cluster centroids
    c. Distance metric
    d. Error rate
    Answer: b. Cluster centroidsaimcqs+1​
29. Which algorithm can separate outliers as their own group?
    a. Agglomerative clustering
    b. K-Means
    c. DBSCAN
    d. Regression
    Answer: c. DBSCANaimcqs+1​
30. What is an advantage of hierarchical clustering?
    a. Requires predefined cluster count
    b. Handles non-numeric data
    c. Produces a tree representation of clusters
    d. Maximizes classification accuracy
    Answer: c. Produces a tree representation of clustersscribd+1​
31. Which clustering method creates a hierarchy of clusters?
    a. K-Means
    b. Agglomerative clustering
    c. DBSCAN
    d. Linear regression
    Answer: b. Agglomerative clusteringaimcqs+1​
32. What is “grouping” mainly used for in genetic research?
    a. Supervised classification
    b. Regression analysis
    c. Identifying similar gene expression patterns
    d. Feature reduction
    Answer: c. Identifying similar gene expression patternsmlexam+1​
33. What type of data is required for clustering algorithms?
    a. Labeled data
    b. Numeric data only
    c. Unlabeled data
    d. Categorical labels
    Answer: c. Unlabeled datageeksforgeeks+1​
34. Which clustering method is iterative and needs convergence criteria?
    a. DBSCAN
    b. Agglomerative clustering
    c. K-Means
    d. Spectral clustering
    Answer: c. K-Meansaimcqs​
35. Which is NOT a use case for grouping in machine learning?
    a. Anomaly detection
    b. Customer segmentation
    c. Predicting stock prices
    d. Document clustering
    Answer: c. Predicting stock pricesgithub+1​
36. What does grouping in machine learning enable in exploratory data analysis?
    a. Hyperparameter tuning
    b. Discovery of hidden patterns
    c. Feature encoding
    d. Label propagation
    Answer: b. Discovery of hidden patternsgeeksforgeeks+1​
37. Which grouping algorithm is highly sensitive to noise and outliers?
    a. DBSCAN
    b. K-Means
    c. Agglomerative clustering
    d. Mean-Shift
    Answer: b. K-Meansyoutube​aimcqs​
38. What is the primary output of a clustering algorithm?
    a. Data labels
    b. Group memberships
    c. Regression coefficients
    d. Feature importances
    Answer: b. Group membershipsaionlinecourse+1​
39. Which grouping algorithm is especially suitable for image segmentation?
    a. Linear regression
    b. K-Means
    c. Logistic regression
    d. Decision tree
    Answer: b. K-Meansmlexam+1​
40. What does a “compact cluster” represent in grouping?
    a. Low similarity among points
    b. Points are close together
    c. Large spread in data
    d. High outlier count
    Answer: b. Points are close togetheryoutube​geeksforgeeks​
41. Which linkage method considers average distance between all pairs in two clusters?
    a. Single linkage
    b. Complete linkage
    c. Average linkage
    d. Ward’s method
    Answer: c. Average linkagealmabetter+1​
42. What is a disadvantage of divisive clustering?
    a. Computationally intensive
    b. Always produces optimal clusters
    c. Works with labeled data
    d. Linear time complexity
    Answer: a. Computationally intensivescribd+1​
43. Which clustering algorithm uses centroids as prototypes for clusters?
    a. Agglomerative clustering
    b. DBSCAN
    c. K-Means
    d. Mean-Shift
    Answer: c. K-Meansmlexam+1​
44. Which type of grouping uses grid-based methods?
    a. Hierarchical clustering
    b. Grid-based clustering
    c. Partition-based clustering
    d. Density-based clustering
    Answer: b. Grid-based clusteringstudyglance+1​
45. Which grouping method is especially beneficial when clusters differ in shape?
    a. K-Means
    b. DBSCAN
    c. Spectral clustering
    d. Agglomerative clustering
    Answer: b. DBSCANstudyglance+1​
46. Which method merges clusters based on the closest distance iteratively?
    a. Agglomerative clustering
    b. Divisive clustering
    c. K-Means clustering
    d. DBSCAN
    Answer: a. Agglomerative clusteringalmabetter+1​
47. What does a dendrogram cutoff determine in hierarchical clustering?
    a. Cluster centroids
    b. Number of clusters
    c. Feature weights
    d. Regression coefficients
    Answer: b. Number of clustersalmabetter+1​
48. Which method uses density and connectivity for grouping?
    a. Agglomerative clustering
    b. DBSCAN
    c. Divisive clustering
    d. K-Means
    Answer: b. DBSCANstudyglance+1​
49. What is the primary task in mean-shift clustering?
    a. Determining feature weights
    b. Identifying density peaks
    c. Predicting labels
    d. Calculating centroid distances
    Answer: b. Identifying density peaksaimcqs+1​
50. Which clustering algorithm is fastest for large datasets?
    a. K-Means
    b. DBSCAN
    c. Mean-Shift
    d. Agglomerative clustering
    Answer: a. K-Meansscribd+1​

1. https://www.geeksforgeeks.org/machine-learning/unsupervised-learning/
2. https://www.mlexam.com/unsupervised-learning/
3. https://aimcqs.com/clustering
4. https://www.youtube.com/watch?v=Oauv8ws342I
5. https://www.scribd.com/document/748348345/Cluster-MCQ
6. https://github.com/Devinterview-io/unsupervised-learning-interview-questions
7. https://www.almabetter.com/bytes/tutorials/gate-data-science-and-ai/unsupervised-learning-for-gate
8. https://www.sanfoundry.com/data-science-questions-answers-clustering/
9. https://www.sanfoundry.com/1000-machine-learning-questions-answers/
10. https://studyglance.in/objquestions/display.php?url=btech%2Fdm-unit-4.txt&title=Data+Mining++MCQs+-+Unit-4&subject=DM&furl=data%2Fbtech%2Fbtechobjquestions.xlsx
11. https://www.aionlinecourse.com/ai-quiz-questions/machine-learning/clustering
12. https://www.gyansetu.in/blog/machine-learning-mcq-interview-preparation/
13. https://gtu-mcq.com/BE/Computer-Engineering/Semester-6/3160714/5460/MCQs?q=9aZHDjblmRk%3D
14. https://www.interviewbit.com/machine-learning-mcq/
15. https://www.scribd.com/document/660661097/5Clustering-Solved-MCQs-of-Clustering-in-Data-mining-with-Answers
16. https://www.mlstack.cafe/blog/unsupervised-learning-interview-questions
17. https://www.placementpreparation.io/mcq/machine-learning/
18. https://www.aionlinecourse.com/ai-quiz-questions/machine-learning/unsupervised-learning
19. https://www.vskills.in/interview-questions/unsupervised-machine-learning-interview-questions
20. https://www.sciencedirect.com/science/article/pii/S1877050920317993