DAV Unit 4 Notes AKTU (BCDS501)

AKTU · BTECH · Semester 5 · Introduction to Data Analytics and Visualization · Unit 4 · Notes

AKTU Introduction to Data Analytics and Visualization (BCDS501) Unit 4 notes for B.Tech Semester 5 – Frequent Itemsets and Clustering. Topics: Frequent…

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Unit 4: Frequent Itemsets and Clustering – AKTU syllabus topics

  • Frequent Itemsets: Mining Frequent Itemsets, Market Based Modelling, Apriori Algorithm
  • Large Data Handling: Main Memory Handling, Limited Pass Algorithm, Frequent Itemsets In Stream
  • Clustering Techniques: Hierarchical Clustering, K Means
  • High Dimensional Clustering: High Dimensional Data, CLIQUE And ProCLUS
  • Advanced Clustering: Pattern Based Clustering, Non Euclidean Clustering, Streams And Parallelism

Most asked AKTU PYQ questions from Unit 4

  1. Q6b. What do you mean by k-means clustering? How does the k-means algorithm work? Write k-meansalgorithm for partitioning. (10 marks, 2022-23)
  2. Q6a. Explain clustering techniques used in data mining. (7 marks, 2025-26)
  3. Q6b. Analyze the working of K-means clustering with an example. (7 marks, 2025-26)
  4. Q6a. For the given data, find the association rule using apriori algorithm. Given: Minimum Support= 2, Minimum Confidence= 50% (10 marks, 2022-23)
  5. Q2d. Explain Apriori algorithm and its role in frequent itemset mining. (7 marks, 2025-26)
  6. Q2d. Compare and contrast hierarchical clustering and K-means clustering. What are the advantages and disadvantages of each? (7 marks, 2024-25)
  7. Q6b. Explain the following- i. Apriori Algorithm ii. Market based modeling (7 marks, 2023-24)
  8. Q5b. Discuss k-means clustering? Explain its working. Write k-means algorithm for partitioning. (7 marks, 2023-24)
  9. Q1f. What is frequent itemset mining? (2 marks, 2025-26)
  10. Q2d. Illustrate with examples CLIQUE and ProCLUS. (7 marks, 2023-24)

AKTU paper codes: BCDS501, KDS501

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