Machine Learning Unsupervised Learning 3

Question 1

What is an autoencoder in the context of unsupervised learning?

Accepted Answer

A neural network trained to reconstruct its input through a bottleneck

Answer

An autoencoder compresses input to a lower-dimensional latent code (encoder) and then reconstructs the original input (decoder).

Question 2

Which linkage criterion in hierarchical clustering tends to produce compact, spherical clusters?

Accepted Answer

Ward linkage

Answer

Ward linkage minimizes the total within-cluster variance at each merge step, producing compact and roughly spherical clusters.

Question 3

What problem does ICA (Independent Component Analysis) solve that PCA does not?

Accepted Answer

Separating statistically independent non-Gaussian source signals

Answer

ICA finds a decomposition into statistically independent components, making it suitable for blind source separation tasks like separating audio signals.

Question 4

What is a dendrogram used for in clustering?

Accepted Answer

Visualizing the hierarchy of cluster merges in agglomerative clustering

Answer

A dendrogram is a tree diagram showing the sequence of merges in hierarchical clustering, helping choose the number of clusters by cutting at a desired height.

Question 5

Which assumption does K-Means make about cluster shapes?

Accepted Answer

Clusters are convex and isotropic (spherical)

Answer

K-Means uses Euclidean distance to assign points to the nearest centroid, implicitly assuming clusters are convex and roughly spherical.

Machine Learning Practice Test

Machine Learning Practice Test

Machine Learning Unsupervised Learning 3