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05 1x22 DATA MINING
Credit : 5


1. Introduction : Motivated Data Mining Data Mining on what kind of Data, Data Mining Functionalities,
Classification of Data Mining System, Major issues in Data Mining.

2. Data Warehouse and OLAP Technology for Data Mining : Data Warehouse, Data Warehouse Architecture, Data Warehouse Implementation, Development of Data cube technology, Data Warehousing to Data Mining.

3. Data Preprocessing : Data cleaning, Data Integration and Transformation, Data Reduction, Discrimination and concept Hierarchy Generation. 

4. Data Mining Primitives, Primitives, Languages and System Architectures : Data Mining Primitives, Data Mining query language, Designing GUI on a Data Mining query language, Architectures of Data Mining System.

5. Mining Association rules in large database : Association rules mining, Mining single-dimensional Boolean Association rules from transaction database, mining multilevel Association rules from transaction database, Mining multidimensional Association rules from relational databases and Data warehouses, Association mining to correlation analysis, Constraint based association mining. 

6. Classification and Prediction : What is classification and prediction, Issues regarding classification and prediction, Classification by decision tree Induction, Bayesian Classification, Classification by Back propagation, Classification based on concepts from association rule mining, Prediction, Classification accuracy. 

7. Cluster Analysis : What is cluster analysis, Types of data in cluster analysis, A categorization of major
clustering methods, Partitioning methods, Hierarchical Methods, Density based methods, Grid based methods, Model based clustering methods. 

8. Applications and trends in Data Mining : Data mining applications, Social impacts of Data Mining, Trends in Data Mining. 

Text Books :
1. Data Mining Concepts and Techniques by Jiawei Han, Micheline Kamber, Elsevier.
2. Data Mining. A tutorial-based Primer by Roiger, Michael W. Geatz and Pearson Education.
3. Data Mining Introductory & advanced topic by Margaret H. Dunham , Pearson Education
Reference Books :
1. Data Mining : Next Generation Challenges and Future Direction by Kargupta, et al, PHI.
2. Data Warehousing, Data Mining & OLAP by Alex Berson Stephen J.Smith.

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