Implementing Data Mining Algorithms In Microsoft Sql Server
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Implementing Data Mining Algorithms in Microsoft SQL Server
"All source codes, as well as data sets used in computational experiments, are included in the accompanying CD-ROM." -- p. [xv]
Microsoft Data Mining
Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database, Commerce Server, and other products, details the Microsoft OLE DB for Data Mining standard, and gives readers best practices for using all of them. The book bridges the previously specialized field of data mining with the new technologies and methods that are quickly making it an important mainstream tool for companies of all sizes.Data mining refers to a set of technologies and techniques by which IT professionals search large databases of information (such as those contained by SQL Server) for patterns and trends. Traditionally important in finance, telecommunication, and other information-intensive fields, data mining increasingly helps companies better understand and serve their customers by revealing buying patterns and related interests. It is becoming a foundation for e-commerce and knowledge management. - Unique book on a hot data management topic - Part of Digital Press's SQL Server and data mining clusters - Author is an expert on both traditional and Microsoft data mining technologies
Data Mining with Microsoft SQL Server 2008
Eine praxisorientierte Einführung in das Data Mining Toolset des SQL Server 2008 und die neuen Data Mining Add-Ins für Office 2007. Enthält detaillierte Erläuterungen und Beispiele zu allen neuen Data Mining Features des SQL Server 2008. Gibt präzise Anleitungen zum Arbeiten mit den wichtigsten Data Mining-Algorithmen, (Naive Bayes-, Decision Trees-, Time Series-, Sequence Clustering-, Association- und Neural Network-Algorithmus), zum Data Mining in OLAP Datenbanken und mit SQL Server Integration Services 2008. Die begleitende Website enthält den kompletten Quellcode zu den Beispielen aus dem Buch.