Applied data mining for forecasting using SAS /

Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Rey, Tim
Autor Corporativo: SAS Institute
Otros Autores: Kordon, Arthur K., Wells, Chip
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cary, N.C. : SAS Institute, 2012.
Temas:
SAS (Computer file)
Data mining.
Forecasting.
Exploration de données (Informatique)
Prévision.
COMPUTERS > Database Management > Data Mining.
Data mining
Forecasting
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Why industry needs data mining for forecasting
  • Data mining for forecasting work process
  • Data mining for forecasting infrastructure
  • Issues with data mining for forecasting application
  • Data collection
  • Data preparation
  • A practitioner's guide to DMM methods for forecasting
  • Model building: ARMA models
  • Model building: ARIMAX or dynamic regression modes
  • Model building: further modeling topics
  • Model building: alternative modeling approaches
  • An example of data mining for forecasting.

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