Stochastic Modeling for Distributed Data Mining - Mani, Manikandan;Kaliyaperumal, Senthamarai Kannan;Venugopal, Deneshkumar
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Data mining and knowledge discovery are powerful data analysis tools for the task of critical applications to minimize, filter, extract or transform large databases or data sets into summarized information and exploring hidden patterns in Knowledge Discovery Database (KDD). Data mining has been applied in several fields such as biological, medicine, industrial, business, economic, e-commerce, security, terrorism and other fields. It provides a means of extracting previously unknown, predictive information from the base of accessible data in data warehouses. It also uses sophisticated and…mehr

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Produktbeschreibung
Data mining and knowledge discovery are powerful data analysis tools for the task of critical applications to minimize, filter, extract or transform large databases or data sets into summarized information and exploring hidden patterns in Knowledge Discovery Database (KDD). Data mining has been applied in several fields such as biological, medicine, industrial, business, economic, e-commerce, security, terrorism and other fields. It provides a means of extracting previously unknown, predictive information from the base of accessible data in data warehouses. It also uses sophisticated and automated algorithms to discover hidden patterns, correlations and relationships among organizational data.
Autorenporträt
M.Manikandan, professeur associé, département de génie électrique et électronique à JYOTHISHMATHI INSTITUTE OF TECHNOLOGY AND SCIENCE, KARIMNAGAR, TELANGANA STATE-505481. S.Ashwanth, professeur adjoint, département de génie électrique et électronique ,Velalar College of Engineering and Technology, Erode, Tamilnadu.