Explain following terms. 1) Data warehouse 2) OLAP 3) Spatial mining 4) Strong rules 5) Outliers 6) Text mining 7) Backpropagation
[7 marks]List the various Data Pre-processing methods. Discuss various Data Cleaning techniques for Missing value and Noisy data.
[7 marks]What is data mining? Describe the steps involved in data mining process with diagram.
[7 marks]Describe the FP-growth (Frequent Pattern growth method) approach for mining frequent itemsets.
[7 marks]What is Apriori property? How the Apriori property is used in finding frequent itemset. Explain Join and Prune step.
[7 marks]Differentiate between two classification methods Eager learners & Lazy learners. Also give the examples of methods of eager learners and lazy learners.
[7 marks]What is Bayes theorem? Explain the working of Naïve Bayesian Classifier.
[7 marks]Describe Decision Tree Induction algorithm. You can describe it with the help of an example. How are the Rules induced from the Decision Tree?
[7 marks]Discuss following in brief: 1) Information Gain 2) Gain Ratio
[7 marks]What is cluster analysis? What are the requirements of cluster analysis?
[7 marks]Compare K-mean and K-medoids methods of clustering.
[7 marks]Write a short note on “Types of data in cluster analysis”.
[7 marks]Discuss the categorization of clustering methods.
[7 marks]Why Data Mining Required for Biological Data Analysis?
[7 marks]Discuss the typical cases of Data Mining in Telecommunication Industry.
[7 marks]Explain Data Mining for Financial Data Analysis.
[7 marks]Discuss typical cases of Data Mining in Retail Industry.
[7 marks]