PCA25S01J · Cycle Test 1
Covers units 1 & 2: Introduction to Data Mining / Association Rule Mining
Answer any 4 questions (4 x 5 = 20 Marks)
Define Data Mining. List any four applications.
What is Data Preprocessing? Why is it important?
Differentiate between structured, semi-structured and unstructured data.
Define Support, Confidence and Lift.
What is Data Visualization? Mention any five visualization techniques?
What is Market Basket Analysis? Give one real-life example?
Answer ALL questions (2 x 15 = 30 Marks)
Explain the Data Mining Process with a neat diagram.
Explain various Data Mining tools and their applications. Compare WEKA, Python, and R.
A supermarket has 100 transactions, 40 transactions contain Milk, 50 transactions contain Bread, and 30 transactions contain both Milk and Bread. Calculate the Support, Confidence, and Lift for the association rule Milk -> Bread.
Explain the Apriori Algorithm with a neat example.