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Outlier Analysis
Charu C. Aggarwal
€ 95.03
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Description for Outlier Analysis
Hardcover. Num Pages: 466 pages, 65 black & white illustrations, 13 colour illustrations, 10 colour tables, biography. BIC Classification: UFM; UNF; UYQP. Category: (P) Professional & Vocational. Dimension: 254 x 178 x 27. Weight in Grams: 1102.
This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories:
This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories:
- Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods.
- Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete ... Read more
- Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner.
- The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.
Product Details
Format
Hardback
Publication date
2016
Publisher
Springer
Condition
New
Number of Pages
466
Place of Publication
Cham, Switzerland
ISBN
9783319475776
SKU
V9783319475776
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Charu C. Aggarwal
Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his undergraduate degree in Computer Science from the Indian Institute of Technology at Kanpur in 1993 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 1996. He has published more than 300 papers in refereed ... Read more
Reviews for Outlier Analysis
“This book presents an extensive coverage on outlier analysis from data mining and computer science perspective. Each chapter includes a detailed coverage of the topics, case studies, extensive bibliographic notes, a number of exercises, and the future direction of research in this field. The book is a good source for researchers also could be used as textbook in the related ... Read more