Textbook on Data Mining

Textbook on Data Mining is a comprehensive textbook that covers the fundamental principles and practices of data mining. The book is written in a clear and concise style, and it is designed to be accessible to students and professionals with a variety of backgrounds, including computer science, information technology, and business.

The book begins with an overview of the field of data mining and its importance in the modern world. It then discusses the different types of data mining tasks, such as classification, clustering, regression, and association rule mining. The book also covers a variety of specific data mining topics, such as:

• Cluster analysis
• Data analysis
• Data analytics
• Data applications
• Data streams
• Frequent pattern mining
• Graph mining
• Outlier analysis
• Privacy-preserving data mining
• Sequence mining
• Social networks
• Spatial data mining
• Text mining
• Time-series analysis
• Web mining

The book also includes a number of chapters on more advanced topics, such as:

• Ensemble learning
• Machine learning
• Natural language processing
• Visual data mining

Subjects / Topics

Computer Science, Data Mining and Knowledge Discovery, Pattern Recognition

Keywords Covered

Cluster analysis, Data analysis, Data analytics, Data applications, Data mining, Data streams, Frequent pattern mining, Graph mining, Outlier analysis, Privacy-preserving data mining, Sequence mining, social networks, Spatial data mining, Text mining, Time-series analysis, Web mining, etc



Pages – 740