Exam Details
| Subject | data mining | |
| Paper | ||
| Exam / Course | mca | |
| Department | ||
| Organization | Gujarat Technological University | |
| Position | ||
| Exam Date | November, 2018 | |
| City, State | gujarat, ahmedabad |
Question Paper
1
Seat No.: Enrolment
GUJARAT TECHNOLOGICAL UNIVERSITY
MCA SEMESTER-IV • EXAMINATION WINTER 2018
Subject Code: 3640006 Date:27/11/ 2018
Subject Name: DATA MINING
Time: 10.30 am to 1.00 pm Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1
Explain following terms.
Data warehouse
OLAP
Spatial mining
Strong rules
Outliers
Text mining
Backpropagation
07
List the various Data Pre-processing methods. Discuss various Data Cleaning techniques for Missing value and Noisy data.
07
Q.2
What is data mining? Describe the steps involved in data mining process with diagram.
07
Describe the FP-growth (Frequent Pattern growth method) approach for mining frequent itemsets.
07
OR
What is Apriori property? How the Apriori property is used in finding frequent itemset. Explain Join and Prune step.
07
Q.3
Differentiate between two classification methods Eager learners Lazy learners. Also give the examples of methods of eager learners and lazy learners.
07
What is Bayes theorem? Explain the working of Naïve Bayesian Classifier.
07
OR
Q.3
Describe Decision Tree Induction algorithm. You can describe it with the help
of an example. How are the Rules induced from the Decision Tree?
07
Discuss following in brief:
Information Gain
Gain Ratio
07
Q.4
What is cluster analysis? What are the requirements of cluster analysis?
07
Compare K-mean and K-medoids methods of clustering.
07
OR
Q.4
Write a short note on "Types of data in cluster analysis".
07
Discuss the categorization of clustering methods.
07
Q.5
Why Data Mining Required for Biological Data Analysis?
07
Discuss the typical cases of Data Mining in Telecommunication Industry.
07
OR
Q.5
Explain Data Mining for Financial Data Analysis.
07
Discuss typical cases of Data Mining in Retail Industry.
07
Seat No.: Enrolment
GUJARAT TECHNOLOGICAL UNIVERSITY
MCA SEMESTER-IV • EXAMINATION WINTER 2018
Subject Code: 3640006 Date:27/11/ 2018
Subject Name: DATA MINING
Time: 10.30 am to 1.00 pm Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1
Explain following terms.
Data warehouse
OLAP
Spatial mining
Strong rules
Outliers
Text mining
Backpropagation
07
List the various Data Pre-processing methods. Discuss various Data Cleaning techniques for Missing value and Noisy data.
07
Q.2
What is data mining? Describe the steps involved in data mining process with diagram.
07
Describe the FP-growth (Frequent Pattern growth method) approach for mining frequent itemsets.
07
OR
What is Apriori property? How the Apriori property is used in finding frequent itemset. Explain Join and Prune step.
07
Q.3
Differentiate between two classification methods Eager learners Lazy learners. Also give the examples of methods of eager learners and lazy learners.
07
What is Bayes theorem? Explain the working of Naïve Bayesian Classifier.
07
OR
Q.3
Describe Decision Tree Induction algorithm. You can describe it with the help
of an example. How are the Rules induced from the Decision Tree?
07
Discuss following in brief:
Information Gain
Gain Ratio
07
Q.4
What is cluster analysis? What are the requirements of cluster analysis?
07
Compare K-mean and K-medoids methods of clustering.
07
OR
Q.4
Write a short note on "Types of data in cluster analysis".
07
Discuss the categorization of clustering methods.
07
Q.5
Why Data Mining Required for Biological Data Analysis?
07
Discuss the typical cases of Data Mining in Telecommunication Industry.
07
OR
Q.5
Explain Data Mining for Financial Data Analysis.
07
Discuss typical cases of Data Mining in Retail Industry.
07
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