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Contemporary Perspectives in Data Mining
Contemporary Perspectives in Data Mining
Knygos.lt klubas Knygos.lt nariams
87,56 €
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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 form this data by examining the patterns of the data, whether they be associations of groups or things, pr…
  • Leidėjas:
  • Metai: 2012
  • Puslapiai: 254
  • ISBN-10: 162396055X
  • ISBN-13: 9781623960551
  • Formatas: 15.6 x 23.4 x 1.4 cm, minkšti viršeliai
  • Kalba: Anglų

Contemporary Perspectives in Data Mining (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 form 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 seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.

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  • Leidėjas:
  • Metai: 2012
  • Puslapiai: 254
  • ISBN-10: 162396055X
  • ISBN-13: 9781623960551
  • Formatas: 15.6 x 23.4 x 1.4 cm, minkšti 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 form 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 seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.

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