IITM MLT Week 3 Questions
K-means Clustering
Week 3 question PDF
Solve clustering questions involving assignments, centroid updates and convergence. Graph-based datasets and distance tables in the PDF support practice with K-means, K-means++ initialization and cluster quality.
The complete question statements, options, numerical data and any supporting graphs or tables are in the PDF. Numbered comprehension questions can include several subquestions. Answer keys are included for checking your attempt; these are not full worked solutions.
Topics covered in this collection
- Lloyd's algorithm and centroid updates
- K-means++ initialization probabilities
- Clustering loss and convergence
- Silhouette scores and cluster evaluation
How to approach these questions
- Separate the assignment step from the centroid update step and repeat until assignments stabilize.
- In K-means++, use squared distances to the closest chosen center when calculating sampling probabilities.
- Read plotted coordinates carefully and use the stated convention when two centers are equally close.
Attempt the questions using the assumptions and notation stated in each problem. For short-answer questions, round only at the final step to the requested precision. Check the provided key after solving and revisit the relevant concept when an answer differs.