2CSE60E15: Data Warehousing & Data Mining

Learning Outcomes: 
Upon Completion of the course, the students will be able to
Store voluminous data for online processing
Preprocess the data for mining applications
Apply the association rules for mining the data
Design and deploy appropriate classification techniques
Cluster the high dimensional data for better organization of the data
Discover the knowledge imbibed in the high dimensional system
Evolve Multidimensional Intelligent model from typical system
Evaluate various mining techniques on complex data objects
Syllabus: 
Unit NoTopics
Introduction

Introduction to Data Mining, Importance of Data Mining, Data Mining functionalities, Classification of Data mining systems, Data mining architecture, Major Issues in Data Mining, Data mining metrics, Applications of Data Mining, Social impacts of data, Data Mining from a Database Perspective

Data Pre-processing

Introduction,Descriptive Data Summarization, Data Cleaning, Data Integration and Transformation, Data Reduction, DataDiscretization.

Classification and Prediction

Basic issues regarding classification and predication, Classification by Decision Tree, Bayesian classification, classification by back propagation, Associative classification, Prediction, Statistical-Based Algorithms, Decision Tree -Based Algorithms, Neural Network -Based Algorithms, Rule-Based Algorithms, Other Classification Methods, Combining Techniques, Classifier Accuracy and Error Measures

Clustering

Similarity and Distance Measures, Hierarchical Algorithms, Partitioned Algorithms, Clustering Large Databases, Clustering with Categorical Attributes

Association Rules

BasicAlgorithms, Advanced Association Rule Techniques, Measuringthe Quality ofRules

Applications and other Data mining techniques

Data Mining Applications, Mining Event Sequences, Visual DM Text Mining, Web Mining, The WEKA data mining Workbench 

Text Books: 
Name : 
Data Mining: Concepts and Techniques
Author: 
J. Han and M. Kamber
Publication: 
Morgan Kaufman
Edition: 
3/E , 2011
Name : 
Data Warehousing, Data Mining, and OLAP
Author: 
Alex Berson, Stephen J. Smith
Publication: 
MGH, 1998.
Syllabus PDF: 
AttachmentSize
PDF icon ELECTIVE V (DWD) .pdf145.65 KB
branch: 
BDA
Course: 
2014
2016
Stream: 
B.Tech