Question 1
Which of the following best describes the concept of clustering in unsupervised learning?
Question 2
In the k-means clustering algorithm, how is the number of clusters (k) determined?
Question 3
Which of the following is a key difference between Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE)?
Question 4
Which metric is commonly used to evaluate the quality of clusters produced by a clustering algorithm when ground truth labels are not available?
Question 5
In Latent Dirichlet Allocation (LDA) for topic modeling, what does the parameter $\alpha$ represent?
