Electronic Resource

Outlier analysis

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With the increasing advances in hardware technology for data collection, and advances in software technology (databases) for data organization, computer scientists have increasingly participated in the latest advancements of the outlier analysis field. Computer scientists, specifically, approach this field based on their practical experiences in managing large amounts of data, and with far fewer assumptions– the data can be of any type, structured or unstructured, and may be extremely large. Outlier Analysis is a comprehensive exposition, as understood by data mining experts, statisticians and computer scientists. The book has been organized carefully, and emphasis was placed on simplifying the content, so that students and practitioners can also benefit. Chapters will typically cover one of three areas: methods and techniques commonly used in outlier analysis, such as linear methods, proximity-based methods, subspace methods, and supervised methods; data domains, such as, text, categorical, mixed-attribute, time-series, streaming, discrete sequence, spatial and network data; and key applications of these methods as applied to diverse domains such as credit card fraud detection, intrusion detection, medical diagnosis, earth science, web log analytics, and social network analysis are covered.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

E1047

Penerbit

New York : Springer., 2013

Deskripsi Fisik

xv, 446 hlm.

Bahasa

English

ISBN/ISSN

9781461463962

Klasifikasi

NONE

Tipe Isi

text

Tipe Media

computer

Tipe Pembawa

online resource

Edisi

-

Subjek

Program Komputer (dan Pemrograman)
Data Mining
Manajemen Database

Info Detail Spesifik

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Pernyataan Tanggungjawab

Charu C. Aggarwal

Versi lain/terkait

Lampiran Berkas

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