Introduction to Data Analytics and Visualization Unit 4 – Frequent Itemsets and Clustering: important questions for AKTU
Unit 4 (Frequent Itemsets and Clustering) questions that AKTU repeats most often. This unit carries about 25 marks per paper. Start with the repeated questions, then the most asked topics.
Most repeated Unit 4 questions
- Explain clustering techniques used in data mining. (7 marks, 2026, Clustering Techniques) – also asked in 2023, 2024, 2025
- Analyze the working of K-means clustering with an example. (7 marks, 2026, Clustering Techniques) – also asked in 2023, 2024, 2025
- What do you mean by k-means clustering? How does the k-means algorithm work? Write k-meansalgorithm for partitioning. (10 marks, 2023, Clustering Techniques) – also asked in 2024, 2025, 2026
Most important Unit 4 topic
- Clustering Techniques (Unit 4: Frequent Itemsets and Clustering) – asked 7 times in 2023, 2024, 2025, 2026
Most asked Unit 4 topics
- Clustering Techniques – asked 7 times
- Frequent Itemsets – asked 6 times
- High Dimensional Clustering – asked 2 times
More Unit 4 previous year questions
- What is frequent itemset mining? (2 marks, 2026, Frequent Itemsets)
- Explain Apriori algorithm and its role in frequent itemset mining. (7 marks, 2026, Frequent Itemsets)
- How do methods like CLIQUE and ProCLUS overcome traditional clustering limitations? (2 marks, 2025, High Dimensional Clustering)
- Compare and contrast hierarchical clustering and K-means clustering. What are the advantages and disadvantages of each? (7 marks, 2025, Clustering Techniques)
- What is parallelism in clustering algorithms? How does it improve performance in handling large datasets? (7 marks, 2025, Advanced Clustering)
Unit 4 syllabus topics
- Frequent Itemsets
- Large Data Handling
- Clustering Techniques
- High Dimensional Clustering
- Advanced Clustering