Ebook: Advanced Data Mining Techniques

This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.

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This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.

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This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.
Content:
Front Matter....Pages I-XII
Front Matter....Pages 1-1
Introduction....Pages 3-8
Data Mining Process....Pages 9-35
Front Matter....Pages 37-37
Memory-Based Reasoning Methods....Pages 39-52
Association Rules in Knowledge Discovery....Pages 53-68
Fuzzy Sets in Data Mining....Pages 69-86
Rough Sets....Pages 87-109
Support Vector Machines....Pages 111-123
Genetic Algorithm Support to Data Mining....Pages 125-135
Performance Evaluation for Predictive Modeling....Pages 137-147
Front Matter....Pages 149-149
Applications of Methods....Pages 151-167
Back Matter....Pages 169-180

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This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focusses on business applications of data mining. Methods are presented with simple examples, applications are reviewed, and relativ advantages are evaluated.
Content:
Front Matter....Pages I-XII
Front Matter....Pages 1-1
Introduction....Pages 3-8
Data Mining Process....Pages 9-35
Front Matter....Pages 37-37
Memory-Based Reasoning Methods....Pages 39-52
Association Rules in Knowledge Discovery....Pages 53-68
Fuzzy Sets in Data Mining....Pages 69-86
Rough Sets....Pages 87-109
Support Vector Machines....Pages 111-123
Genetic Algorithm Support to Data Mining....Pages 125-135
Performance Evaluation for Predictive Modeling....Pages 137-147
Front Matter....Pages 149-149
Applications of Methods....Pages 151-167
Back Matter....Pages 169-180
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