Contemporary Perspectives in Data Mining

Volume 3

Nonfiction, Computers, Advanced Computing, Information Technology, Business & Finance, Finance & Investing, Finance, Reference & Language, Education & Teaching
Cover of the book Contemporary Perspectives in Data Mining by , Information Age Publishing
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Author: ISBN: 9781641130561
Publisher: Information Age Publishing Publication: September 1, 2017
Imprint: Information Age Publishing Language: English
Author:
ISBN: 9781641130561
Publisher: Information Age Publishing
Publication: September 1, 2017
Imprint: Information Age Publishing
Language: English
The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.

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