Bihar Engineering University, Bihar, Computer Engineering Semester 8, Data Mining Syllabus

Unit - 1 Introduction

Unit – 1

Introduction

1.1 Motivated Data Mining Data Mining on what kind of Data

1.2 Data Mining Functionalities

1.3 Classification of Data Mining System

1.4 Major issues in Data Mining

Unit - 2 Data Warehouse and OLAP Technology for Data Mining

Unit – 2

Data Warehouse and OLAP Technology for Data Mining

2.1 Data Warehouse

2.2 Data Warehouse Architecture

2.3 Data Warehouse Implementation

2.4 Development of Data cube technology

2.5 Data Warehousing to Data Mining

Unit - 3 Data Preprocessing

Unit – 3

Data Preprocessing

3.1 Data cleaning

3.2 Data Integration and Transformation

3.3 Data Reduction

3.4 Discrimination and concept Hierarchy Generation.

Unit - 4 Data Mining Primitives, Primitives, Languages and System Architectures

Unit – 4

Data Mining Primitives Primitives Languages and System Architectures

4.1 Data Mining Primitives

4.2 Data Mining query language

4.3 Designing GUI on a Data Mining query language

4.4 Architectures of Data Mining System

Unit - 5 Mining Association rules in large database

Unit – 5

Mining Association rules in large database

5.1 Association rules mining

5.2 Mining singledimensional Boolean

5.3 Association rules from transaction database

5.4 Mining multilevel Association rules from transaction database

5.5 Mining multidimensional Association rules from relational databases and Data warehouses

5.6 Association mining to correlation analysis

5.7 Constraint based association mining

Unit - 6 Classification and Prediction

Unit – 6

Classification and Prediction

6.1 What is classification and prediction

6.2 Issues regarding classification and prediction

6.3 Classification by decision tree Induction

6.4 Bayesian Classification

6.5 Classification based on concepts from association rule mining

6.6 Prediction

6.7 Classification accuracy

Unit - 7 Cluster Analysis

Unit 7

Cluster Analysis

7.1 What is cluster analysis

7.2 Types of data in cluster analysis

7.3 A categorization of major clustering methods

7.4 Partitioning methods

7.5 Hierarchical Methods

7.6 Density based methods

7.7 Grid based methods

7.8 Model based clustering methods

Unit - 8 Applications and trends in Data Mining

Unit – 8

Applications and trends in Data Mining

8.1 Data mining applications

8.2 Trends in Data Mining.