WITH EFFECT FROM THE ACADEMIC YEAR 2013–2014
CS-451
DATA MINING
Instruction 4 Periods per week
Duration of University Examination 3 Hours
University Examination 75 Marks
Sessional 25 Marks
UNIT-I
Introduction: Fundamentals of Data Mining, Kinds of Patterns can be mined, Technologies Used, Applications and Issues in Data Mining
Types of Data: Attribute types, Basic Statistical descriptions of Data, Measuring data Similarity and Dissimilarity
Data Preprocessing: Need of Preprocessing, Data Cleaning, Data Integration, Data Reduction, Data Transformation
UNIT-II
Data Warehouse and OLAP: Data Warehouse, Data Warehouse Modeling, Data Warehouse Design and Usage, Data Warehouse Implementation, Data Generalization by Attribute-oriented induction
UNIT-III
Mining Frequent Patterns, Associations and Correlations: Market Basket Analysis, Association rule mining, Frequent Item set mining methods, Pattern Evaluation methods, Constraint based frequent pattern mining, Mining Multilevel and Multidimensional patterns
UNIT-IV
Classification : General approach to classification, Classification by Decision Tree Induction , Bayes Classification methods, Bayesian Belief Networks, Classification by Backpropogation, Lazy Learners, Other Classification methods , Classification using Frequent patterns, Model Evaluation and selection
UNIT-V
Cluster Analysis: Basic Clustering methods, Partitioning methods, Density –Based Methods, Grid-based methods, and Evaluation of Clustering, Outlier Analysis and Detection methods
Data Mining Trends and Research Frontiers: Mining Complex Data Types, Data Mining Applications, Data Mining Trends
Suggested Reading:
1. Data Mining – Concepts and Techniques - Jiawei Han & Micheline Kamber and Jain Pei, Third Edition, India ( 2011).
References:
1. Data Mining Introductory and advanced topics – Margaret H Dunham, Pearson
education
2. Data Mining Techniques – Arun K Pujari, University Press.
3. Data Warehousing in the Real World – Sam Anahory & Dennis Murray Pearson Edn
4. Data Warehousing Fundamentals – Paulraj Ponnaiah Wiley Student ed.
5. The Data Warehouse Life cycle Tool kit – Ralph Kimball Wiley student edition.