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About this product
- DescriptionNew techlogies have enabled us to collect massive amounts of data in many fields. However, our pace of discovering useful information and kwledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains a comprehensive set of data mining algorithms from various data mining fields. The book reviews theoretical rationales and procedural details of data mining algorithms, including those commonly found in the literature and those presenting considerable difficulty, using small data examples to explain and walk through the algorithms. The book covers a wide range of data mining algorithms, including those commonly found in data mining literature and those t fully covered in most of existing literature due to their considerable difficulty. The book presents a list of software packages that support the data mining algorithms, applications of the data mining algorithms with references, and exercises, along with the solutions manual and PowerPoint slides of lectures. The author takes a practical approach to data mining algorithms so that the data patterns produced can be fully interpreted. This approach enables students to understand theoretical and operational aspects of data mining algorithms and to manually execute the algorithms for a thorough understanding of the data patterns produced by them.
- Author BiographyNong Ye is Professor of Industrial Engineering at Arizona State University in Tempe.
- Author(s)Nong Ye
- PublisherTaylor & Francis Inc
- Date of Publication02/08/2013
- SubjectComputing: Professional & Programming
- Series TitleHuman Factors and Ergonomics
- Place of PublicationBosa Roca
- Country of PublicationUnited States
- ImprintCRC Press Inc
- Content Note57 black & white illustrations, 68 black & white tables
- Weight635 g
- Width156 mm
- Height234 mm
- Spine25 mm
- Format DetailsUnsewn / adhesive bound
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