Explain various OLAP operations.
[3 marks]Compare Linear and nonlinear regression.
[4 marks]Explain Star, Snowflake and Fact constellation” schemas of data warehouse with suitable example. Q .2 (a ) Define the following terms: 0 1. OLAP 2. OLTP 3. OLAM
[3 marks]What is data mining integration in data warehousing? Explain with an example
[4 marks]Discuss data discretization and concept hierarchy generation.
[7 marks]Explain Naïve Bayesian classification in detail with example.
[7 marks]Define techniques to improve the efficiency of Apriori algorithm.
[3 marks]Define nominal and ordinal variables
[4 marks]What is data transformation? Explain the different data transformation approaches for transforming data.
[7 marks]What is feature selection in data mining?
[3 marks]Define Fact Table and dimension table.
[4 marks]What is the confusion matrix, and how is it used to evaluate a classifier?
[7 marks]Define Support & Confidence.
[3 marks]Discuss Issues regarding Classification and prediction
[4 marks]Describe and explain the different types of clustering methods.
[7 marks]What is outlier? Discuss different methods for outlier detection.
[3 marks]Explain the difference between a data warehouse and a data mart
[4 marks]What are the reasons for the presence of ‘noise’ in data collected for mining? Explain the methods to deal with noise.
[7 marks]Define data mart.
[3 marks]What is association rule mining? Explain with an example.
[4 marks]What is Decision Tree? Explain how classification is done using decision tree induction.
[7 marks]What is a data cube?
[3 marks]Discuss the limitations and challenges of data mining
[4 marks]Explain Web Mining in detail.
[7 marks]