Tuesday, August 4, 2009

Data mining concepts and techniques Jiawei Han and Micheline Kambe

Data mining concepts and techniques
Jiawei Han and Micheline Kamber




for ppts click below
Chapter 1. Introduction

Chapter 2. Data Warehouse and OLAP Technology for Data Mining

Chapter 3. Data Preparation

Chapter 4. Data Mining Primitives, Languages, and System Architectures

Chapter 5. Concept Description: Characterization and Comparison

Chapter 6. Mining Association Rules in Large Databases (compressed)

Chapter 7. Classification and Prediction

Chapter 8. Cluster Analysis

Chapter 9. Mining Complex Types of Data

Chapter 10. Data Mining Applications and Trends in Data Mining

Appendix A. An Introduction to Microsoft's OLE DB for Data Mining

Appendix B. An Introduction to DBMiner

Data mining books for ISE and CSE VTU

INTRODUCTION TO DATA MINING - Pang Ning Tan , Michael Steibach ,Vipin kumar

1. Introduction (lecture slides: [PPT] [PDF])


2. Data (lecture slides: [PPT][PDF])

3. Exploring Data (lecture slides: [PPT][PDF])


4. Classication: Basic Concepts, Decision Trees, and Model Evaluation (lecture slides: [ PPT][PDF]
)

5. Classication: Alternative Techniques (lecture slides: [PPT][PDF])

6. Association Analysis: Basic Concepts and Algorithms (lecture slides: [PPT][PDF])

7. Association Analysis: Advanced Concepts (lecture slides: [PPT][PDF])

8. Cluster Analysis: Basic Concepts and Algorithms (lecture slides: [PPT][PDF])


9. Cluster Analysis: Additional Issues and Algorithms (lecture slides: [PPT][PDF])

10. Anomaly Detection (lecture slides: [PPT][PDF])



Book Figures in PowerPoint Slide Format:

1. Introduction (figure slides: [PPT])

2. Data (figure slides: [PPT])

3. Exploring Data (figure slides: [PPT])

4. Classication: Basic Concepts, Decision Trees, and Model Evaluation (figure slides: [ PPT])

5. Classication: Alternative Techniques (figure slides: [PPT])

6. Association Analysis: Basic Concepts and Algorithms (figure slides: [PPT])

7. Association Analysis: Advanced Concepts (figure slides: [PPT])

8. Cluster Analysis: Basic Concepts and Algorithms (figure slides: [PPT])

9. Cluster Analysis: Additional Issues and Algorithms (figure slides: [PPT])

10. Anomaly Detection (figure slides: [PPT])

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