Outlier Analysis,Used

Outlier Analysis,Used

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SKU: SONG3319475770
Brand: Springer
Condition: Used
$48.55
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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, proximitybased methods, highdimensional (subspace) methods, ensemble methods, and supervised methods. Domainspecific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, timeseries data, discrete sequence data, spatial data, and network data. 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, oneclass supportvector machines, matrix factorization, neural networks, outlier ensembles, timeseries methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

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