Unsupervised Learning Algorithms MCQs
1. Which of the following is an unsupervised learning algorithm?
a. Decision tree
b. K-means clustering
c. Random Forest
d. Support Vector Machines (SVM)
Answer: b. K-means clustering
2. In unsupervised learning, the training dataset consists of:
a. Input features only
b. Output labels only
c. Input features and output labels
d. None of the above
Answer: a. Input features only
3. Which unsupervised learning algorithm is used for dimensionality reduction?
a. Principal Component Analysis (PCA)
b. Decision tree
c. Naive Bayes
d. Linear Regression
Answer: a. Principal Component Analysis (PCA)
4. The main objective of clustering algorithms in unsupervised learning is to:
a. Predict continuous values
b. Determine the optimal number of clusters
c. Assign input data to predefined categories or classes
d. Identify patterns in unlabeled data
Answer: b. Determine the optimal number of clusters
5. Which unsupervised learning algorithm is based on the concept of "nearest neighbors"?
a. K-means clustering
b. Hierarchical clustering
c. Naive Bayes
d. K-nearest neighbors (KNN)
Answer: b. Hierarchical clustering
6. Which algorithm is used to identify patterns or relationships in unlabeled data?
a. Decision tree
b. Association rule mining
c. K-means clustering
d. Principal Component Analysis (PCA)
Answer: b. Association rule mining
7. Which unsupervised learning algorithm is used for outlier detection?
a. Logistic Regression
b. Decision tree
c. Support Vector Machines (SVM)
d. Isolation Forest
Answer: d. Isolation Forest
8. Which algorithm is used for finding similar items or grouping similar data points together?
a. K-means clustering
b. Random Forest
c. Support Vector Machines (SVM)
d. Nearest Neighbors
Answer: d. Nearest Neighbors
9. Which unsupervised learning algorithm is used for market basket analysis?
a. Apriori algorithm
b. Decision tree
c. Naive Bayes
d. Linear Regression
Answer: a. Apriori algorithm
10. Which algorithm is used for recommendation systems?
a. Linear Regression
b. Decision tree
c. Collaborative Filtering
d. Multinomial Logistic Regression
Answer: c. Collaborative Filtering
11. Which unsupervised learning algorithm is used for finding the underlying structure or patterns in data?
a. K-means clustering
b. Random Forest
c. Principal Component Analysis (PCA)
d. Naive Bayes
Answer: c. Principal Component Analysis (PCA)
12. Which algorithm is used for text document clustering?
a. K-means clustering
b. Decision tree
c. Naive Bayes
d. Hierarchical clustering
Answer: a. K-means clustering
13. Which unsupervised learning algorithm is used for density estimation?
a. Linear Regression
b. Decision tree
c. Gaussian Mixture Models (GMM)
d. Support Vector Machines (SVM)
Answer: c. Gaussian Mixture Models (GMM)
14. Which algorithm is used for dimensionality reduction while preserving the neighborhood
relationships of the data points?
a. K-means clustering
b. Random Forest
c. t-distributed Stochastic Neighbor Embedding (t-SNE)
d. Support Vector Machines (SVM)
Answer: c. t-distributed Stochastic Neighbor Embedding (t-SNE)
15. Which unsupervised learning algorithm is used for market segmentation?
a. Linear Regression
b. Decision tree
c. K-means clustering
d. Naive Bayes
Answer: c. K-means clustering
16. Which algorithm is used for anomaly detection in unsupervised learning?
a. Linear Regression
b. Decision tree
c. Support Vector Machines (SVM)
d. Isolation Forest
Answer: d. Isolation Forest
17. Which unsupervised learning algorithm is used for finding frequent itemsets?
a. Linear Regression
b. Decision tree
c. Apriori algorithm
d. Naive Bayes
Answer: c. Apriori algorithm
18. Which algorithm is used for clustering data points based on their density?
a. K-means clustering
b. DBSCAN
c. Support Vector Machines (SVM)
d. Nearest Neighbors
Answer: b. DBSCAN
19. Which unsupervised learning algorithm is used for data visualization?
a. Principal Component Analysis (PCA)
b. Decision tree
c. Naive Bayes
d. Linear Regression
Answer: a. Principal Component Analysis (PCA)
20. Which algorithm is used for finding association rules among items in a transactional dataset?
a. K-means clustering
b. Random Forest
c. Association rule mining
d. Support Vector Machines (SVM)
Answer: c. Association rule mining
21. Which unsupervised learning algorithm is used for image compression?
a. Linear Regression
b. Decision tree
c. K-means clustering
d. Naive Bayes
Answer: c. K-means clustering
22. Which algorithm is used for community detection in social network analysis?
a. Linear Regression
b. Decision tree
c. Spectral Clustering
d. Multinomial Logistic Regression
Answer: c. Spectral Clustering
23. Which unsupervised learning algorithm is used for data imputation?
a. Linear Regression
b. Decision tree
c. Expectation-Maximization (EM) algorithm
d. Support Vector Machines (SVM)
Answer: c. Expectation-Maximization (EM) algorithm
24. Which algorithm is used for generating synthetic samples in unsupervised learning?
a. Linear Regression
b. Decision tree
c. Variational Autoencoder (VAE)
d. Naive Bayes
Answer: c. Variational Autoencoder (VAE)
25. Which unsupervised learning algorithm is used for document topic modeling?
a. Linear Regression
b. Decision tree
c. Latent Dirichlet Allocation (LDA)
d. Support Vector Machines (SVM)
Answer: c. Latent Dirichlet Allocation (LDA)
26. Which algorithm is used for clustering data points based on their connectivity?
a. K-means clustering
b. Random Forest
c. Mean Shift
d. Nearest Neighbors
Answer: c. Mean Shift
27. Which unsupervised learning algorithm is used for reducing the dimensionality of text data?
a. Principal Component Analysis (PCA)
b. Decision
tree
c. Latent Semantic Analysis (LSA)
d. Naive Bayes
Answer: c. Latent Semantic Analysis (LSA)
28. Which algorithm is used for discovering sequential patterns in unsupervised learning?
a. Linear Regression
b. Decision tree
c. Hidden Markov Models (HMM)
d. Support Vector Machines (SVM)
Answer: c. Hidden Markov Models (HMM)
29. Which unsupervised learning algorithm is used for market basket analysis with transaction weighting?
a. Linear Regression
b. Decision tree
c. Weighted Association rule mining
d. Naive Bayes
Answer: c. Weighted Association rule mining
30. Which algorithm is used for density-based clustering that can handle non-linearly separable data?
a. Linear Regression
b. Decision tree
c. OPTICS
d. Support Vector Machines (SVM)
Answer: c. OPTICS