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portada Outlier Analysis
Type
Physical Book
Publisher
Year
2016
Language
English
Pages
466
Format
Hardcover
ISBN13
9783319475776
Edition No.
2

Outlier Analysis

Charu C. Aggarwal (Author) · Springer · Hardcover

Outlier Analysis - Charu C. Aggarwal

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Synopsis "Outlier Analysis "

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 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, 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. 

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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.

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