MS-DS Master of Data science MS-DS Master of Data science Unsupervised Learning Techniques Questions and Answers 3

Question 1

What advantage does DBSCAN have over K-Means for spatial data with irregular cluster shapes?

Accepted Answer

DBSCAN can discover clusters of arbitrary shape based on density

Answer

DBSCAN groups together densely connected points regardless of cluster geometry, making it effective for non-convex and irregularly shaped clusters.

Question 2

In K-Means clustering, what problem can arise from poor centroid initialization?

Accepted Answer

Convergence to a suboptimal local minimum

Answer

Poor initialization can cause K-Means to converge to a local minimum rather than the global optimum, resulting in suboptimal cluster assignments.

Question 3

Which linkage criterion in hierarchical clustering measures the distance between the closest members of two clusters?

Accepted Answer

Single linkage

Answer

Single linkage defines inter-cluster distance as the minimum distance between any pair of points from the two clusters, which can produce elongated chain-like clusters.

Question 4

What is the role of the covariance matrix in a Gaussian Mixture Model?

Accepted Answer

It captures the shape, orientation, and spread of each Gaussian component

Answer

Each component's covariance matrix defines the ellipsoidal shape, orientation, and spread of that Gaussian distribution in the feature space.

Question 5

What does the reconstruction error of an autoencoder indicate about the input data?

Accepted Answer

How well the compressed representation captures the essential features of the input

Answer

Reconstruction error measures the difference between the original input and the autoencoder's output, indicating how effectively the bottleneck layer preserves important information.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science MS-DS Master of Data science Unsupervised Learning Techniques Questions and Answers 3