4. Machine Learning

Unsupervised Learning — Quiz

Test your understanding of unsupervised learning with 5 practice questions.

Practice Questions

Question 1

When applying K-Means clustering to a business dataset, which of the following initializations is most likely to lead to suboptimal clustering results due to its sensitivity to outliers and density variations?

Question 2

A retail company wants to identify distinct customer segments based on their purchasing behavior using unsupervised learning. After applying a clustering algorithm, they obtain clusters with varying sizes and non-spherical shapes. Which clustering algorithm would be most appropriate for this scenario?

Question 3

In the context of dimensionality reduction for business analytics, if a dataset has $P$ features and we apply Principal Component Analysis (PCA) to reduce it to $K$ principal components, which of the following statements about the variance explained by the principal components is true?

Question 4

A marketing analyst is using Latent Dirichlet Allocation (LDA) for topic modeling on a large collection of customer feedback documents. Which of the following is a key assumption of LDA that might impact the interpretation of the discovered topics?

Question 5

Consider a scenario where a business wants to detect fraudulent transactions in a large, unlabeled dataset. They are looking for rare occurrences that deviate significantly from the majority of normal transactions. Which unsupervised learning technique is most suitable for this anomaly detection task?