STUPIDSID
1 (a)
Define Business intelligence and decision support systems with examples.
10 M
1 (b)
Explain Data mining as a step in KDD. Give the architecture of typical Data Mining system.
10 M
2 (a)
Explain BIRCH algorithm with example.
10 M
2 (b)
Explain different visualization techniques that can be used in data mining.
10 M
3 (a)
Explain Multilevel association rules with suitable examples.
10 M
3 (b)
Define classification, issues of classification and explain ID3 classification with example.
10 M
4 (a)
Why is Data Preprocessing required? Explain the different steps involved in data preprocessing.
10 M
4 (b)
What is text mining? Explain different approaches to text mining.
10 M
5 (a)
Explain Business Intelligence Issues.
10 M
5 (b)
What is clustering? Explain k-means clustering algorithm. Suppose the data for clustering - {2, 4, 10, 12, 3, 20, 11, 25}. Consider k=2, cluster the given data using above algorithm.
10 M
6 (a)
Explain sequence mining in Transactional database.
10 M
6 (b)
Design a BI system for fraud detection by describing all the steps from Data Collection to Decision Making.
10 M
More question papers from Data Mining & Business Intelligence