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Contemporary Perspectives in Data Mining Volume 4
Contemporary Perspectives in Data Mining Volume 4
Knygos.lt klubas Knygos.lt nariams
159,38 €
-30%
Įprastai
227,69 €
  • Išsiųsime per 12–18 d.d.
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, pre…
  • Leidėjas:
  • ISBN-10: 1648021441
  • ISBN-13: 9781648021442
  • Formatas: 15.6 x 23.4 x 1.1 cm, kieti viršeliai
  • Kalba: Anglų

Contemporary Perspectives in Data Mining Volume 4 (el. knyga) (skaityta knyga) | knygos.lt

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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 business (banking, brokerage, and insurance), marketing (customer relationship, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security and law enforcement.


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  • Leidėjas:
  • ISBN-10: 1648021441
  • ISBN-13: 9781648021442
  • Formatas: 15.6 x 23.4 x 1.1 cm, kieti viršeliai
  • Kalba: Anglų


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 business (banking, brokerage, and insurance), marketing (customer relationship, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security and law enforcement.


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