Description
| Product ID: | 9780128117606 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | US |
| Series: | The Morgan Kaufmann Series in Data Management Systems |
| Title: | Data Mining |
| Subtitle: | Concepts and Techniques |
| Authors: | Author: Hanghang Tong, Jiawei Han, Jian Pei |
| Page Count: | 752 |
| Subjects: | Library, archive and information management, Library, archive & information management, Social and ethical issues, Medical and health informatics, Enterprise software, Algorithms and data structures, Data capture and analysis, Data mining, Artificial intelligence, Expert systems / knowledge-based systems, Computer vision, Social interaction, Medical bioinformatics, Enterprise software, Algorithms & data structures, Data capture & analysis, Data mining, Artificial intelligence, Expert systems / knowledge-based systems, Computer vision |
| Description: | Select Guide Rating Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining. |
| Imprint Name: | Morgan Kaufmann Publishers In |
| Publisher Name: | Elsevier Science & Technology |
| Country of Publication: | GB |
| Publishing Date: | 2022-10-26 |
